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object(Timber\Post)#3711 (44) { ["ImageClass"]=> string(12) "Timber\Image" ["PostClass"]=> string(11) "Timber\Post" ["TermClass"]=> string(11) "Timber\Term" ["object_type"]=> string(4) "post" ["custom"]=> array(5) { ["_wp_attached_file"]=> string(12) "R_103KRR.pdf" ["wpmf_size"]=> string(7) "1101878" ["wpmf_filetype"]=> string(3) "pdf" ["wpmf_order"]=> string(1) "0" ["searchwp_content"]=> string(222610) "Fiscal Effects of Voter Approval Requirements on Local Governments ••• Kim S. Rueben Pedro Cerdán 2003 PUBLIC POLICY INSTITUTE OF CALIFORNIA Library of Congress Cataloging-in-Publication Data Rueben, Kim S. Fiscal effects of voter approval requirements on local governments / Kim S. Rueben, Pedro Cerdán. p. cm. Includes bibliographical references. ISBN: 1-58213-065-5 1. Local revenue—California. 2. Local elections—California. I. Cerdán, Pedro, 1978- II. Title. HJ9204.R84 2003 336'.014794—dc21 2002154263 Copyright © 2003 by Public Policy Institute of California All rights reserved San Francisco, CA Short sections of text, not to exceed three paragraphs, may be quoted without written permission provided that full attribution is given to the source and the above copyright notice is included. PPIC does not take or support positions on any ballot measure or state and federal legislation nor does it endorse or support any political parties or candidates for public office. Research publications reflect the views of the authors and do not necessarily reflect the views of the staff, officers, or Board of Directors of the Public Policy Institute of California. Foreword Between 1978 and 2000, California voters did not make life easy for local governments. The passage of Proposition 13 in 1978, for example, had a chilling effect on local revenues. Likewise, the passage of Proposition 218, which required that any new general tax or fee measure achieve a two-thirds majority vote, did little to aid local efforts to raise funds. For these governments, the only good news along these lines came in 2000, when the passage of Proposition 39 lowered the supermajority needed for school bond approval to 55 percent. With this recent history in mind, Kim Rueben and Pedro Cerdán have tracked patterns in local fiscal measures between 1986 and 2002. Although their findings certainly do not suggest a profligate electorate, eager to raise taxes for local services, they do reveal broad patterns in the willingness to fund certain services. Their study also explores more specific fiscal questions. Which local governments are more likely to use the ballot box to raise revenues? Which have actually succeeded? What kinds of ballot measures have the highest success rate? In general, the authors found that measures that fund specific services—especially school facilities, transportation, and fire protection—have higher approval rates than those that fund general services. In contrast, proposals to fund parks and libraries are rather less likely to succeed; as a result, these traditional public services are more likely to go unfunded. This report gives us a fresh understanding of how the fiscal limitation movement has affected local public finance in California since the mid1980s. Although the long-term consequences of its findings are not fully understood, the reader is left with two impressions: Local voters are still actively determining their own fiscal fate, and some cities and segments of the state’s population are in danger of being left behind. David W. Lyon President and CEO Public Policy Institute of California iii iv Summary California public finance has become increasingly complicated over the last 25 years. Because local officials now need voter approval to pass a growing set of local taxes, local governments, especially counties and school districts, have become more dependent on state funds to provide local services. As the economy weakens and current public finance instruments raise less money, local governments again face hard decisions about how to pay for needed services—services that the public wants or that local governments are required to provide but that voters do not necessarily want to pay for with new or increased taxes. Limitations on local government revenue sources started with Proposition 13 in 1978, which limited property tax rates and the ability of local governments to increase assessed property values and to pass special taxes. Since then, several initiatives and court decisions have also affected the fiscal authority of local governments, usually increasing the role voters play in determining revenue sources. For example, Proposition 218, passed in 1996, required voter approval for any new general taxes, fees, and assessments. This report examines the ways local jurisdictions (school districts, cities, and other local governments) have used the ballot box to pass new taxes or gain approval for capital bond measures. The findings indicate substantial variation in voter reaction to such fiscal measures, depending on region, timing, the type of measure proposed, and the local service to be funded. This information should prove useful to local officials who must decide whether and how to raise revenues in their jurisdictions. From 1986 to 2000, California voters were asked to pass local tax and bond measures over 2,500 times. About two-thirds of local fiscal measures were for taxes and fees, and they passed at a rate of 42 percent. The other one-third were bond authorization requests, which passed at the slightly higher rate of 48 percent. Most bond measures were proposed and passed by school districts, and school districts primarily v proposed bond measures rather than tax measures. In contrast, other local governments were more likely to propose tax measures. California has experienced an increase in the number of fiscal measures since 1996. This increase is related to increased demand for school infrastructure spending leading to increased rates of school district bond proposals. This trend accelerated in the aftermath of Proposition 39—a state measure passed in 2000 that lowered the supermajority needed to pass school bonds to 55 percent. Tax measures also increased in occurrence and in passage rates, reflecting the need for voter approval for general taxes and certain fees and assessments beginning in 1996. We examine five questions in this report: 1. How have statewide restrictions on local governments influenced the relationship between state and local governments? Specifically, how have they affected which level of government raises funds to provide local services? We find that following the passage of Proposition 13 in 1978, county and school districts became increasingly reliant on other levels of government, most notably the state, to raise funds to provide local services. In California, the amount of money spent by local governments raised by own-source revenue (revenue that is raised and spent by the same level of government) fell from 58 percent in 1977 to 50 percent in 1997. In contrast, local governments in the rest of the country became increasingly reliant on own-source funds, increasing their use from 57 percent to 62 percent. County governments in California went from raising half of all their funds in 1977 to raising only 36 percent of funds from own-source revenues by 1997. In the rest of the country, counties increased their reliance on own-fund sources from 57 to almost 70 percent over the same period. School districts have become increasingly reliant on state funds in both California and the rest of the country, but these changes were more dramatic in California. Cities and special districts in California raise most of their funding through local sources and have consequently been more reliant on local approval of new measures and the use of fees and assessments. vi 2. To what extent have governments used the ballot box to raise new funds? What choices have local governments made in response to statewide restrictions on how revenue is raised and the need for local approval? Local governments have proposed multiple measures to raise revenues including bonds, parcel taxes, business or consumer taxes, hotel room taxes, and sales taxes. An increasing number of local governments used ballot measures to raise new taxes, but most of them did not use the ballot box repeatedly. Although a few local governments, most notably those in the Bay Area, proposed multiple measures, most local governments requested voter approval for new funds only occasionally and stopped after one successful election. School districts were most likely to propose bond measures, although most districts that proposed bond measures passed only one. More school districts proposed and passed bonds following the passage of Proposition 39, which lowered the supermajority required for passage from two-thirds to 55 percent. Cities were most likely to propose tax measures, although almost half of all cities proposed no measures and only one-third of cities successfully passed a ballot measure. Use of ballot measures increased for cities and counties after 1996 and the explicit requirement of voter approval for general taxes. We find that passage rates depended on which services were to be funded, with transportation and emergency service measures passing most often and recreation and park measures passing least often. We also find distinct regional patterns. Governments in the Bay Area and the southern regions of the state proposed measures most often, and the Bay Area measures passed at a higher rate than measures elsewhere. Finally, measures proposed by special districts passed at a higher rate than city or county measures—even when they funded the same function. 3. In the case of school districts, how do restrictions on funding sources interact with legal requirements for spending equity? Does the use of local ballot measures lead to differences in current or capital expenditures? vii School districts are highly reliant on local bond measures to fund infrastructure spending. About one-third of school construction and modernization funds came from bond measures. Most school districts passed only one bond measure and often returned to the ballot box until successful. Support for school bond elections has been growing in recent years, with a higher percentage of school bonds being proposed and passing even before the passage of Proposition 39 (Figure S.1). Following Proposition 39, 32 school districts proposed bond measures in November 2001, of which 29 passed. In March 2002, 67 out of 76 bond measures passed, and in November 2002, 103 bond measures were proposed and 84 passed. In the late 1990s, the amount of money raised to pay for school facility construction was strongly related to both enrollment and assessed valuations; districts with higher assessed value raised more money. Constitutional limits on the amount of debt school districts can incur are directly based on assessed value within a district. Thus, wealthier 120 100 80 60 40 20 0 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 NOTES: Each period is one-third of a year. The year labels correspond to the third period, including the November general election. Figure S.1—Number of Bond Measures Proposed by School Districts, 1986–2002 viii Number of measures districts can raise more money if a bond measure is successful. Furthermore, matching programs for state funds have exacerbated differences in spending levels across school districts. Indeed, as voters recently approved $13.05 billion in state bond funds for education facilities by passing Proposition 47 and the state is proposing another $12.25 billion in 2004, it may be important to reexamine how state funds are allocated. Capital expenditures are not subject to equity requirements as set forth under court decisions about school finance equalization, but may be called into question in current court cases. School districts can propose parcel taxes to raise more money for current expenditures. These taxes raise a given amount of money per property and are not based on assessed value. Tax measures were proposed much less frequently by school districts and were approved in only 55 school districts. They usually were for less than $200 per parcel and lasted for a limited period of time. School districts that have passed a parcel tax measure will often approve another measure as the first tax expires. Parcel taxes were most often proposed by Bay Area school districts; they were also used by small school districts with high-income households and high property values. Districts that successfully passed a parcel tax spent approximately $600 (about 8 percent of current expenditures) more per student in 1999–2000 than other school districts (about 60 percent of this spending difference was directly related to parcel taxes). Although these differences in spending levels were not directly related to assessed value differences in districts, wealthier districts were more likely to pass these measures. 4. What characteristics differentiate municipalities that have succeeded in passing fiscal measures from those that have not? Can we explain spending disparities by the passage of new taxes, or do they reflect underlying differences in cities? Municipal governments have become less reliant on the property tax, but overall revenues have not declined for two groups of cities: those that never proposed ballot measures and those that successfully passed a ballot measure. When we examine which cities went to the ballot box and which cities approved new tax measures, we find that cities that relied more on property taxes historically were more likely to ask for and ix receive authorization to implement new tax measures. We also find that proposal and passage rates were higher in cities with a high percentage of registered Democrats. Larger cities and cities in the Bay Area were also more likely to ask for and receive voter approval for new tax measures. On average, cities that proposed a ballot measure but were unsuccessful at passing a new tax had lower revenues before Proposition 13 passed, and those revenue-level differences widened over time. When we compare the three sets of California cities—those that never proposed tax measures, those that passed new tax measures, and those that proposed but failed to pass tax measures—we find different fiscal outcomes. Figure S.2 shows per capita average revenue for each type of city. We find that these disparities are partly related to the direct effect of passing ballot measures, but they are also related to differences in the characteristics of these groups of cities. Most notably, cities that were unsuccessful had historically raised less revenue, especially from assessments and fees, had a lower percentage of voters registered as Democrats, and had lower household income than those that successfully passed a tax measure. 1,200 1,000 Did not propose Proposed and did not pass Proposed and passed Revenue dollars (2000) 800 600 400 200 0 1987 1992 1997 Figure S.2—Average Per Capita General Revenue, by Measure Outcome, 1987, 1992, and 1997 x We also find that the relationship between city population demographics and the level of revenues raised has changed over time. City government funds have become increasingly dependent on household mobility, with cities having fewer families living in the same house as five years earlier on average raising more money, because of more frequent reassessment of property to market value. This revenue difference results because of Proposition 13, which limits reassessments to when property is sold. Therefore, of two cities with the same market value for property and given increasing housing prices, the city with more frequent turnover will have higher property tax revenues because assessed values will be closer to market values. 5. Are certain levels of government better able to pass new measures? What kinds of taxes tend to pass once they are placed on the ballot and do other characteristics of the elections affect passage rates? We find differences in passage rates across types of governments, even when timing, type of tax proposed, use of tax, and regions are controlled for. Controlling for all other factors, county tax measures passed 32 percent of the time, city measures passed 40 percent of the time, and special district elections passed 47 percent of the time. This pattern may be due to the more specific targets of special district elections. Certain uses of funds and certain types of taxes have higher passage rates all else equal. Transportation measures passed 56 percent of the time, whereas park measures passed an estimated 29 percent of the time. Similarly, after controlling for other characteristics, we find that hotel taxes and other business taxes passed 56 percent of the time and consumer taxes passed 36 percent of the time. Our findings suggest that if popular programs such as transportation measures or fire protection require funding, a dedicated tax, despite the required supermajority for approval, is more likely to garner voter support than a general tax. There are limitations to proposing special taxes, as these funds are earmarked for specific spending areas and therefore will reduce local officials’ flexibility. When controlling for changes in what is placed on the ballot, passage rates have not changed significantly since 1996. Although more xi measures have been proposed, these new measures are not any more or less likely to pass. This result is due to the lower passage rate required (a simple majority) being offset by higher voter preference for funding some specific and more popular functions. We also find that tax measures are more likely to pass if proposed in off-cycle elections. There has been a growing use of ballot measures following passage of Proposition 218 in 1996, which codified the requirement for voter approval for all general taxes. Although voters are playing an increasingly important role in the fiscal decisionmaking process, they are willing to approve new funding sources. Voters are more likely to pass tax measures proposed by special districts and cities than by counties. In general, voters appear more willing to support specific services or construction that they feel will be of direct use to them. Thus, it is important for officials to specify the use of new funds when writing ballot measures. However, voter preferences may leave some traditional government services inadequately funded. For example, transportation and fire services usually receive voter support, but passage is spotty for library services or parks. For cities and counties interested in raising general funds, the type of tax proposed also affects passage rates. The general tax instruments with the highest chance of passage are those that homeowners do not pay directly (i.e., hotel taxes or business taxes). The history of statewide initiatives also illustrates that voters become concerned when they feel that local governments are circumventing voters’ advisory role. For example, the growing use of fees and miscellaneous charges led to Proposition 218, which returned to voters the final authority on these revenue sources. xii Contents Foreword..................................... iii Summary..................................... v Figures ...................................... xv Tables ....................................... xvii Acknowledgments ............................... xxi 1. INTRODUCTION ........................... 1 2. HISTORY OF LOCAL REVENUE RESTRICTIONS .... A Brief History of Local Tax Reform and Restrictions...... Local Fiscal Measures in California.................. California and U.S. Local Government Finances ......... 5 5 11 13 3. SCHOOL DISTRICT ELECTIONS AND THEIR EFFECT ON REVENUES ...................... School District Bond Elections .................... Bond Measures Since the Passage of Proposition 39 ..... Regional Patterns in Bond Elections ............... Distribution of Bond Measures Across School Districts ... Determinants of School District Bond Elections and Capital Expenditures ....................... School District Parcel Tax Elections ................. Regional Patterns in Parcel Tax Elections ............ Distribution of Tax Measures Across School Districts .... Determinants of School District Tax Elections and Current Revenues ......................... Summary .................................. 19 19 21 23 26 28 36 39 40 42 44 4. CITY FISCAL MEASURE ELECTIONS AND THEIR EFFECT ON REVENUES ...................... Municipal Bond Elections ....................... Regional Patterns in Bond Elections ............... Distribution of Bond Measures Across Municipalities .... 47 48 50 51 xiii Determinants of Municipal Government Bond Elections and Capital Revenues ....................... Municipal Tax Elections ........................ Tax Measures Since Passage of Proposition 218 ........ Regional Patterns in Municipal Tax Elections ......... Distribution of Tax Measures Across Municipalities ..... Determinants of Municipal Tax Elections and Current Revenues ............................... Summary .................................. 5. COUNTY AND SPECIAL DISTRICT USE OF THE BALLOT BOX .............................. County Use of the Ballot Box ..................... County Bond Elections ....................... County Tax Elections ........................ Regional Patterns in County Tax Measures ........... Special District Use of the Ballot Box ................ Bond Elections Held by Special Districts ............ Regional Patterns in Special District Bond Elections ..... Tax Elections Held by Special Districts ............. Regional Patterns in Special District Tax Elections ...... Ballot Use Across Different Types of Governments ....... Summary .................................. 6. POLICY CONSIDERATIONS ................... 52 53 56 57 58 59 68 69 69 71 71 74 76 76 77 78 80 83 90 93 Appendix A. Information on Local Measures .................... 97 B. Fiscal Information ............................ 103 C. School District Information ...................... 107 D. Municipal Election Information ................... 115 E. County and Special District Election Information ........ 121 Bibliography .................................. 129 About the Authors ............................... 133 Related PPIC Publications .......................... 135 xiv Figures S.1. Number of Bond Measures Proposed by School Districts, 1986–2002........................ viii S.2. Average Per Capita General Revenue, by Measure Outcome, 1987, 1992, and 1997 ................ x 2.1. Real Per Capita General Revenue, All Local Governments ............................. 15 2.2. Real Per Capita Own-Source General Revenue, All Local Governments ............................. 15 3.1. Number of Bond Measures Proposed by School Districts, 1986–2002........................ 20 3.2. Passage Rate of Bond Measures Proposed by School Districts, 1986–2002........................ 21 3.3. Number of Bond Measures Proposed by School Districts, 1986–2000........................ 24 3.4. Passage Rate of Bond Measures Proposed by School Districts, 1986–2000........................ 25 3.5. Average Total Capital Revenue and Bond Revenue per Student, 1992–2000 ........................ 32 3.6. Number of Parcel Tax Measures Proposed by School Districts, 1986–2002........................ 38 3.7. Passage Rate of Parcel Tax Measures Proposed by School Districts, 1986–2002........................ 38 3.8. Number of Parcel Tax Measures, by School District, 1986–2000 .............................. 40 4.1. Number of Bond Measures Proposed by Municipal Governments, 1986–2000 .................... 49 4.2. Passage Rate of Bond Measures Proposed by Municipal Governments, 1986–2000 .................... 50 4.3. Number of Fiscal Measures, by Type.............. 54 4.4. Passage Rate of Fiscal Measures, by Type ........... 56 4.5. Average Per Capita General Revenue, by Measure Outcome, 1972–1997 ....................... 61 xv 4.6. Estimated Probability of Proposing and Passing a Tax Measure, by Region ........................ 66 4.7. Estimated Real Per Capita General Revenue for a City with Average Demographics ................... 67 5.1. Percentage of 1997 Direct Expenditures Controlled by Counties ............................... 70 5.2. Countywide Measures, by Type of Tax ............ 73 5.3. Passage Rate of Countywide Measures, by Type of Tax ................................... 74 5.4. Number of Special Districts, 1997 ............... 77 5.5. Number of Tax Measures Proposed by Special Districts ................................ 81 5.6. Passage Rate of Tax Measures Proposed by Special Districts, Total............................ 82 5.7. Number of Total Tax Measures Proposed, by County ... 85 5.8. Passage Rate of Tax Measures Proposed, by County .... 86 B.1. Real Per Capita General Revenue for Cities, 1972–1997 .............................. 105 xvi Tables 2.1. Ballot Measure Requirements for Local Revenues in California ............................... 2.2. Per Capita Revenue in California and the Rest of the United States ............................. 3.1. Distribution of Bond Measures Proposed and Passed by School Districts, by Type, 1986–2000 ........... 3.2. Number of Bond Measures Proposed and Passed by School Districts Since Passage of Proposition 39 ...... 3.3. Number of Bond Measures Proposed and Passed, by Region, 1986–2002 ........................ 3.4. Distribution of Bond Measures Proposed by School Districts, 1986–2000........................ 3.5. Distribution of Bond Measures Passed by School Districts, 1986–2000........................ 3.6. Demographic Characteristics of School Districts, by Bond Measure Experience .................... 3.7. School District Per Pupil Capital Revenue, by Bond Measure Experience ........................ 3.8. Estimated Change in Probability of Proposing and Passing Bond Measures ...................... 3.9. Distribution of Parcel Tax Measures Proposed and Passed by School Districts, by Type, 1986–2000 ...... 3.10. Distribution of Parcel Tax Measures Proposed and Passed by School Districts, by Region, 1986–2000 ..... 3.11. Distribution of Parcel Tax Measures Proposed by School Districts, 1986–2000 ................... 3.12. Distribution of Parcel Tax Measures Passed by School Districts, 1986–2000........................ 3.13. Demographic Characteristics of School Districts, by Parcel Tax Experience, 1986–2000 ............... 3.14. Fiscal Characteristics of School Districts, by Parcel Tax Experience, 1986–2000 ...................... 12 16 20 22 23 26 27 30 32 34 37 39 41 41 43 44 xvii 4.1. Number of Bond Measures Proposed and Passed, by Function, 1986–2000 ....................... 4.2. Number of Bond Measures Proposed and Passed, by Timing, 1986–2000 ........................ 4.3. Number of Bond Measures Proposed and Passed, by Region, 1986–2000 ........................ 4.4. Distribution of Bond Measures Proposed by Cities, 1986–2000 .............................. 4.5. Distribution of Bond Measures Passed by Cities, 1986– 2000 .................................. 4.6. Demographic and Fiscal Characteristics of Cities, by Bond Measure Experience, 1986–2000 ............ 4.7. Number of Tax Measures Proposed and Passed, by Function, 1986–2000 ....................... 4.8. Number of Tax Measures Proposed and Passed, by Timing................................. 4.9. Number of Tax Measures Proposed and Passed, by Region, 1986–2000 ........................ 4.10. Distribution of Tax Measures Proposed by Municipal Governments, 1986–2000 .................... 4.11. Distribution of Tax Measures Passed by Municipal Governments, 1986–2000 .................... 4.12. Demographic Characteristics of Cities, by Tax Measure Experience, 1986–2000 ...................... 4.13. Fiscal Characteristics of Cities, by Tax Measure Experience, 1986–2000 ...................... 4.14. Estimated Change in Probability of Proposing and Passing Tax Measures ....................... 5.1. Number of Bond Measures Proposed and Passed by Counties, by Function, 1986–2000 .............. 5.2. Number of Bond Measures Proposed and Passed by Counties, by Region, 1986–2000 ................ 5.3. Number of Tax Measures Proposed and Passed by Counties, by Function, 1986–2000 .............. 5.4. Number of Tax Measures Proposed and Passed by Counties, by Timing ........................ 5.5. Number of Tax Measures Proposed by Counties, by Region and Function ........................ 48 50 51 51 52 53 54 57 58 59 59 60 62 64 71 72 72 74 75 xviii 5.6. Passage Rates of Tax Measures, by Region and Function ............................... 75 5.7. Number of Bond Measures Proposed and Passed, by Type of Jurisdiction ........................ 78 5.8. Number of Bond Measures Proposed and Passed by Special Districts, by Timing ................... 78 5.9. Number of Bond Measures Proposed and Passed by Special Districts, by Region ................... 79 5.10. Number of Tax Measures Proposed and Passed, by Type of Jurisdiction ............................ 79 5.11. Number of Tax Measures Proposed and Passed by Special Districts, by Timing ................... 80 5.12. Number of Tax Measures Proposed, by Region and Type of Special District .......................... 82 5.13. Passage Rates of Tax Measures, by Region and Type of Special District............................ 83 5.14. Number of Measures Proposed and Passed, by Region... 84 5.15. Number of Bond and Tax Measures Proposed and Passed, by Function ........................ 87 5.16. Number of Bond and Tax Measures Proposed and Passed, by Timing.......................... 88 5.17. Estimated Change in Probability of Passing Tax Measures ............................... 89 A.1. Number of Measures, by Source and Type .......... 98 A.2. Number of Measures, by Source, Type, and Year ...... 99 A.3. Number of Measures, by Source, Type, and Year, Excluding School District Elections .............. 100 A.4. Number of Cities, by Election Cycle Timing ........ 101 A.5. School District Elections, by Type of Measure and Timing................................. 102 B.1. Comparison of Cities in and out of Sample ......... 104 C.1. Number of School Districts and Number of Bond Measures Proposed and Passed, by County, 1986–2002 .............................. 108 C.2. Determinants of Bond Measure Proposals and Passage Rates, Regression Results ..................... 110 C.3. Distribution of Key Regression Variables ........... 111 xix C.4. Determinants of Per Pupil Capital Revenue, 1992– 2000 .................................. 112 C.5. Number of Parcel Tax Measures Proposed and Passed by School Districts, by County, 1986–2000 ........... 113 D.1. Number of Tax Measures Proposed and Passed by Cities, 1986–2000 .............................. 116 D.2. Determinants of Tax Measure Proposals and Passage Rates, Regression Results ..................... 118 D.3. Distribution of Key Regression Variables ........... 120 D.4. Demand for City Revenues, Controlling for Which Cities Proposed and Passed Tax Measures........... 120 E.1. Percentage of Direct Expenditures Controlled by Counties, Number of Special Districts, and Number of Tax Measures Proposed and Passed by Special Districts, 1986–2000 .............................. 122 E.2. Number of Tax Measures Proposed and Passed by Non– School District Local Governments, by County, 1986– 2000 .................................. 124 E.3. Determinants of Number of Measures Proposed and Passed by Counties, 1986–2000 ................. 126 E.4. Determinants of the Probability of a Tax Measure Passing................................. 127 xx Acknowledgments We would like to thank Mark Baldassare, Gary Hart, Paul Lewis, John Mockler, Joyce Peterson, Steven Sheffrin, Fred Silva, and Jon Sonstelie for their thoughtful reviews of this manuscript. We would also like to express our appreciation to the California Realtors Association, CASH, and CDIAC for providing us with data on tax and bond measures, with a special thanks to Hardy Gumnor for being especially helpful. We would also like to thank Mary Sprague, Elizabeth Berko, and Sun Kim for help in compiling and organizing the local measure data and Marianne Bitler, Elisa Barbour, Cynthia Gustafson, and Tracy Gordon for help in organizing and accessing the Census of Governments data. This work relies on two companion studies: Therese McGuire collaborated on an earlier article about local tax measures and cities and Edmund Balsdon and Eric Brunner collaborated on work related to school district bond elections. Patricia Bedrosian and Peter Richardson assisted with editorial comments. Abby Cook and Victoria Pike Bond helped with media outreach and meetings with local officials. Our other colleagues at PPIC also provided valuable comments on earlier drafts and at seminars about this topic. Deborah Reed was instrumental in helping us complete a first draft of this report. The report also benefited from meetings with local government officials, especially at the County Auditors conference in 2002. Although this report reflects the contributions of many people, the authors are solely responsible for its content. Any opinions or interpretations expressed are those of the authors and do not necessarily reflect the views of the Public Policy Institute of California. xxi 1. Introduction The passage of Proposition 13 in 1978 marked the beginning of a sea change in the fiscal powers and responsibilities of local governments in California, moving greater control over local government finances to the ballot box through direct voter control.1 In addition to severely limiting property taxes, Proposition 13 also required voter approval for special taxes. In the 25 years that followed, subsequent statewide initiatives extended the voter approval requirement to additional categories of taxes and charges and recently changed the requirements for approval of bond measures. These initiatives were designed to give voters a larger voice in the spending and revenue decisions of cities, counties, school districts, and special districts. The initiatives’ proponents envisioned a choice between seeking voter approval and curtailing spending. In practice, however, using the ballot box to raise revenues is only one possible response of local governments to voter approval requirements. Another is for the state government to play a larger role in raising funds to provide local services. Local officials could also turn to revenue sources that do not require voter approval. When Proposition 13 required approval for special taxes, local governments increased their reliance on general taxes, fees, and assessments. Subsequent statewide initiatives then sought to require voter approval for these alternative funding sources. Much attention has been paid to history surrounding the passage of Proposition 13, its effect on overall government spending in California, and its influence on property values in California.2 However, little of ____________ 1We use local government to refer to nonstate and nonfederal levels of government—counties, cities, special districts, and school districts. 2See, for example, Sears and Citrin (1985), O’Sullivan, Sexton, and Sheffrin (1995), Schrag (1998), and Doerr (2000). These authors occupy many positions on the political spectrum and give different interpretations of circumstances leading up to Proposition 13 and its consequences. 1 this work has examined differences across local governments caused by the provisions in Proposition 13 and subsequent initiatives that expanded voters’ control over revenue sources. To investigate the interaction of voter approval requirements and the fiscal pressures facing local governments, this report studies school districts and city governments— the levels of local governments the electorate is most likely to interact with, where basic government services including public education and police and fire protection are typically provided. School districts usually used the ballot box to pass bond measures to pay for school facilities. This reflects the shifting control of current school spending to the state level following court cases requiring spending equity, whereas capital expenditures (which are funded largely through bonds) remain primarily a local responsibility. However, calls for spending equality in facilities may add another level of complication for school districts. Cities are heavily dependent on local taxes and have used the ballot box far more frequently to propose new tax measures.3 Expanding on the existing literature on Proposition 13, this report examines the proposition’s overall effect on local revenues. It then evaluates the tradeoffs facing local governments between using the ballot box to raise revenues, restricting revenue levels, and finding alternative funding strategies. Although we focus on school districts and cities, we also briefly discuss the use of alternative measures by counties and special districts. We seek to answer five basic questions: 1. How have statewide restrictions on local governments influenced the relationship between state and local governments? Specifically, how have they affected which level of government raises funds to provide local services? 2. To what extent have governments used the ballot box to raise new funds? What choices have local governments made in response to statewide restrictions on how revenue is raised and the need for local approval? ____________ 3In contrast, county governments serve many functions including acting as an agent of the state by providing certain services (such as public assistance or court functions) and municipal services in unincorporated areas. Because of these varying roles, we limit our comparisons of counties but we do discuss county elections in Chapter 5. 2 3. In the case of school districts, how do restrictions on funding sources interact with legal requirements for spending equity? Does the use of local ballot measures lead to differences in current or capital expenditures? 4. What characteristics differentiate municipalities that have succeeded in passing fiscal measures from those that have not? Can we explain spending disparities by the passage of new taxes, or do they reflect underlying differences in cities? 5. Are certain levels of governments better able to pass new measures? What kinds of taxes tend to pass once they are placed on the ballot and do other characteristics of the elections affect passage rates? The report is organized as follows: Chapter 2 examines the legislative and initiative history surrounding local governments’ ability to raise funds and describes aggregate uses of ballot measures. We also compare California’s local government revenue levels to those in the rest of the country and examine aggregate changes in funding responsibility before and after the passage of Proposition 13. Chapter 3 focuses on school districts, exploring school bond and parcel tax measures and their influence on revenue levels. Chapter 4 focuses on cities, briefly analyzing the use of bond measures but mainly exploring the use of tax measures and the types of funds used to provide local services. Chapter 5 expands our analysis to consider tax and bond measures for counties and special districts. Examining the role of other governments is particularly important in California because of the differential reliance on special districts and county governments. We then explore how these differences affect the use of the ballot box, examining overall regional patterns and exploring which services are more likely to gain voter approval for new taxes. Finally, Chapter 6 explores the ramifications of the growing need for voter approval to fund public services. 3 2. History of Local Revenue Restrictions Local governments in California face a complicated set of restrictions on their ability to raise funds and provide services to their residents. In this chapter, we provide a brief history of local finance sources and discuss how these sources have been authorized and limited over time by both the legislature and voters. We are concerned with state-level restrictions (often initiatives placed on the ballot by voters) that require local voter approval before local governments can collect certain revenues. We refer to such ballot measures as local measures. We first describe these statewide restrictions and then discuss our set of local fiscal measures. Finally, we present some evidence on the aggregate changes in local revenue sources. The cumulative effect of these restrictions has been twofold: Most new local efforts to raise revenue require voter approval, and some types of local governments increasingly rely on the state for funding. A Brief History of Local Tax Reform and Restrictions The first constraint on local government revenue appeared in the state constitution in 1879 and required the approval of two-thirds of voters for any general obligation debt for any local agency. As part of constitutional reform in 1911, California adopted practices that allowed for direct legislation by permitting state and local initiatives and referenda. Voters have used these direct democracy instruments in more recent years to approve several statewide initiatives that limit local governments’ ability to impose taxes or fees for local purposes, to authorize local general obligation debt, or to lower the passage requirement for school district bonds. 5 In 1978, Proposition 13 became the most consequential tax limit passed as of that time, but it was not voter groups’ and public officials’ first attempt to limit taxes. Increasing assessed values for property, increased state surpluses, and a court mandate to equalize school district spending across the state all contributed to the passage of Proposition 13. Tax reform proposals appeared throughout the 1960s and 1970s both as ballot measures and as tax plans proposed by the assembly and the governor.1 Often, these proposals were very complicated and hard for voters or legislators to understand. In addition, some were defeated because of uncertainty as to where replacement funds would come from. Doerr (2000) provides a thorough description of these early ballot measures. In 1972, a successful tax reform bill (SB 90) was supposed to provide property tax relief to homeowners and satisfy court rulings concerning education finance equity. The relevant provisions of SB 90 for local governments were property tax rate limits for cities, counties, and special districts and revenue limits for school districts. State aid was increased to school districts to equalize school district spending and to decrease school district reliance on the property tax. This last provision was in part a response to the Serrano v. Priest lawsuit that was winding its way through the courts. The Serrano court case and rulings found that differences in school spending related to differences in assessed values of property were unconstitutional.2 SB 90 also increased homeowners’ exemption levels, provided some tax relief to renters, and increased the state sales tax by 1 percentage point to help pay for these changes. However, SB 90 did not place any limits on how often property would be reassessed. Property tax bills reflect both the tax rates imposed and the level of assessment, so if property values increased and were reassessed relatively often, property tax bills would increase unless property tax rates were lowered. ____________ 1At least four prior initiatives were placed on the ballot, including three sponsored by Howard Jarvis or Paul Gann, the co-sponsors of Proposition 13, and Proposition 1, sponsored by then-Governor Ronald Reagan. 2See Sonstelie, Brunner, and Ardon (2000) for a discussion of school finance reform following the Serrano decision. 6 In the period leading up to 1978, property values and property tax bills were rising quickly.3 At the same time, California’s state government had a large and growing surplus resulting from a combination of increases in inflation and a lack of income tax indexing.4 Thus, when Proposition 13 was placed on the ballot, voters were paying higher property tax bills and the state had an estimated $5 billion surplus that could be used to compensate for revenue losses associated with cuts in property tax rates. In the period leading up to passage of Proposition 13, separate reform bills were going through the two houses of the legislature. However, in 1977 legislators in the two houses and the governor could not agree on a specific tax relief plan. Once Proposition 13 qualified for the ballot, the governor and the legislature proposed a competing measure. Proposition 8 was less straightforward than Proposition 13 and did not offer property tax relief to all homeowners. Following an ill-timed mailing of property tax bills including large increases in property values in Los Angeles, Proposition 13 passed by nearly a 2-1 margin.5 Proposition 13 required a two-thirds vote for any increase in property taxes up to 1 percent of assessed value. It restricted the overall property tax to a maximum of 1 percent of assessed value plus an adjustment for servicing outstanding debt. Proposition 13 also required a two-thirds vote for any increase in taxes for special-purpose use. In ____________ 3State legislation was passed mandating property reassessment to market rates on a timely (often three-year) basis—with assessments being a consistent percentage of market rates. This was in response to a series of scandals uncovered by the San Francisco Chronicle concerning assessors who were accepting payoffs for lower assessments. See Doerr (2000) for more details about this controversy. 4California had a very progressive income tax structure, which meant that as individuals and businesses earned higher income, a larger percentage of funds were necessary to pay state taxes. However, the rise in income taxes in the late 1970s mainly resulted from rising inflation rates, so although nominal incomes were rising, the real amount a family could buy with a given amount of money was not and the lack of indexing led to a real increase in the amount of taxes paid. Thus, families were able to afford fewer things even with higher income levels. The lack of indexing was common across most states and in the federal government—indexing of tax schedules was introduced in California in 1978. 5Doerr (2000) and Schrag (1998) provide detailed accounts of the debate leading up to Proposition 13. They provide very different perspectives on the period and mainly focus on statewide effects. 7 addition, it rolled back assessed property valuations to their 1975 levels, allowing only a 2 percent annual increase in assessed valuation until a property is sold, at which point it is reassessed to market value. After passage of Proposition 13, the state legislature had to decide how to distribute the newly restricted funds and pass implementing legislation. The state’s plan effectively consolidated revenues at the county level and distributed them to local governments in proportion to their funds in 1975–1976. The state also replaced school district funds and then reallocated the revenue from property taxes earmarked for schools to other county governments until 1991. The property tax, which had been the main source of local revenues, effectively became a state-controlled tax in California. Thus, the distribution of property tax revenues is based essentially on the one in place in 1975. Therefore, although the state has changed dramatically over the last 25 years— increasing in both population and diversity—the distribution of property tax revenues within a county has not changed substantially. Proposition 13 did allow property tax rates to exceed 1 percent to pay for existing debt service, although the proposition was not clear on whether the exception could be applied to debt incurred after 1978. Proposition 46, passed in June 1986, allowed voters to increase the property tax above the 1 percent maximum for a limited amount of time to pay for debt service on new general obligation bonds passed with the approval of a two-thirds majority vote. Thus, from 1978 to 1986, local governments were not sure how they would pay back new debt and thus curtailed infrastructure projects that would have been funded with bond revenues. Court cases in the early 1980s also raised questions as to what types of governments were restricted by Proposition 13 and what kinds of taxes required voter approval. For example, were special districts not dependent on the property tax covered by Proposition 13? Did they require voter approval for new revenues? Were new general purpose local taxes covered? The responses to these questions and the increase in alternative funding sources led Howard Jarvis to place another initiative on the ballot in 1984 (Proposition 36) that was defeated by voters. Proposition 36, called the “Save Prop. 13” initiative, would have limited non–ad valorem taxes, required any local tax to be approved by a two- 8 thirds vote of the people, and limited governments’ use of fees.6 This was followed by Proposition 62, which was passed in 1986. Proposition 62 prevented the imposition of new general taxes by local agencies without (majority) voter approval. Unlike Proposition 13, which changed the state constitution, Proposition 62 was a statutory initiative. Its statutory nature led to challenges by charter cities who claimed, and courts upheld, that a charter city’s right to impose general taxes was protected by the home rule powers granted in the state constitution and could not be limited by a statutory measure. The validity of Proposition 62 was also challenged by noncharter localities. In 1995, the California Supreme Court reversed earlier lower court decisions and found Proposition 62 to be constitutional and valid for noncharter local governments. The debate about the application of Proposition 62 as a statutory initiative also ended with the passage of Proposition 218 in 1996. Proposition 218, proposed by the Howard Jarvis Taxpayers Association, amended the state constitution to require that a majority of voters approve any increase in general taxes. In addition, Proposition 218 required property-related assessments, fees, and charges to be submitted either to property owners for majority approval or to voters for twothirds majority approval. This latter requirement addressed the criticism that tax restrictions had led to a renaming of taxes as fees and assessments, which did not require voter approval. Proposition 62 and Proposition 218 covered general taxes and required a simple majority vote, whereas Proposition 13 referred to “special” taxes and required a two-thirds majority vote. Special taxes are those imposed by a city, county, school district, or special district to fund a specific service; general taxes are those raised to fund general government services. What constitutes a special tax has also been the subject of litigation, and the courts have made ambiguous and sometimes contradictory decisions, especially concerning taxes proposed by special districts, which are created to provide a specific service but are typically funded from general funds. Court cases have found that any tax passed ____________ 6For a complete description of the restrictions on local governments that would have been imposed by Proposition 36, see Doerr (2000). 9 by a special district is a special tax and requires a two-thirds majority vote. New court challenges are currently under way concerning which fees and assessments are covered under Proposition 218. Finally, Proposition 37, an initiative proposed but not passed on the November 2000 ballot, explicitly specified which fees and assessments would need voter approval. Other legislative actions that have affected local revenue sources include the Mello-Roos Act of 1982, which provided for the creation of community facilities districts (CFDs). These districts allow for specific services for individuals and properties within the district, and taxes (almost always parcel taxes or fees and assessments) are levied to pay for these services. The state legislature also allowed a local sales tax at a uniform rate of 1 percent, a 0.25 percent county transportation tax rate, and local add-on rates for specific purposes—with voter approval—that are not to exceed an additional 1 percent.7 Because several special funding regulations apply specifically to school districts, we will review the voter requirements and limits for school districts. Following the passage of Proposition 13, and until 1986, school districts were unable to pass local bond measures and relied primarily on state money to fund school construction and modernization. Proposition 46, passed in 1986, reestablished the authority of school districts (along with other local governments) to issue general obligation bonds subject to the approval of two-thirds of voters in the district. In 1986, the state legislature authorized school districts to directly impose developer fees to finance new school construction.8 Before 1986, school districts had no independent authority to impose developer fees and were reliant on city or county officials. School districts were able to form CFDs under the Mello-Roos Act of 1982, which allowed school districts to create smaller areas over which fees could be assessed to pay for new school construction. Proposition 39, ____________ 7For more information on local government tax powers, see California Senate Committee on Local Governments (1996). 8Fees can be imposed only on new developments. The maximum fee is $1.50 per square foot for residential development and $0.25 per square foot for commercial and industrial development. 10 passed in 2000, lowered the voter approval threshold for facilities financing from two-thirds to 55 percent.9 Finally, in addition to the direct restrictions on both tax and bond financing, California voters have restricted the growth rate in expenditures for both state and local governments. Proposition 4, also known as the Gann Initiative, was passed in 1979 and constitutionally restricted the growth rate of expenditures of each level of government to the growth rate in state population and inflation. If revenues exceed this level, the government is required to rebate the excess. However, voters can agree to override the expenditure limit with a simple majority approval. In this report, we do not cover expenditure limit override measures because of limited information on this type of local ballot measure. We do have information on the use of expenditure override measures from 1987 to 1992. Over this period, 161 measures were proposed and 142 overrides passed. Thus, if existing tax instruments raise more money than raised in prior years because of changes in economic circumstance, voters appear to be willing to let local governments keep these funds. The combination of initiatives, constitutional requirements, court decisions, and legislation has led to differences in the level of voter majority that is required for passage of different types of fiscal measures. Table 2.1 summarizes the restrictions in place in California and the margin needed to pass new taxes and bonds. Local Fiscal Measures in California Although ballot measures are playing a growing role in the functioning of local governments in California, there is no single, comprehensive source of information on them. We have compiled information on local ballot measures that relate to new taxes and new bonds from November 1986 to November 2000. Our sources include the California Association of Realtors, the California Debt and ____________ 9Proposition 39 placed additional accountability requirements on school districts that took advantage of this lower passage rate requirement. In addition, this lower passage rate requirement is allowed only during primary or general elections held to elect officials and sets a maximum on the amount that can be approved at any single election. 11 Table 2.1 Ballot Measure Requirements for Local Revenues in California State Constitution (1879) Two-thirds voter approval to issue general obligation debt Proposition 13 (1978) Two-thirds voter approval needed to increase property taxes to 1 percent Maximum property tax of 1 percent except for outstanding debt in 1978; may temporarily exceed maximum for new debt after Proposition 46 (1986) Two-thirds voter approval to impose or increase taxes for special-purpose use Proposition 4, the Gann Initiative (1979) Majority voter approval to allow revenue growth to exceed a limit defined by the growth of state population and state personal income Propositions 62 (1986, effective 1996) and 218 (1996) Majority voter approval to increase taxes or to impose new taxes for general-purpose use Majority property owner or two-thirds voter approval to impose or increase property- related assessments and fees Proposition 39 (2000) 55 percent voter approval for school district bonds subject to election timing restrictions and accountability decisions Investment Advisory Commission, the California Association for Adequate School Housing (CASH), Internet searches of local newspaper stories and websites, and communication with county offices. Appendix A provides a more complete description of these sources of ballot measure data. Our data are comprehensive for school districts but potentially incomplete for city, special district, and county elections during the 1993, 1995, and 1997 election years and for off-cycle elections. On-cycle elections are those held concurrently with statewide general or primary elections. These occur in even years when there are gubernatorial or presidential elections.10 Our analysis suggests that tax measures are less likely to arise in off-year and off-cycle elections. ____________ 10For a discussion of the role that election timing plays in city elections, see Hajnal et al. (2002). 12 Indeed, we find that cities with off-cycle mayoral elections are no more likely to be categorized as never having a tax measure proposed than cities that have their elected positions filled during on-cycle elections. In addition, we have collected preliminary information on school bond elections in 2001 and 2002. We use these data to describe the importance of measures as a fiscal tool of local governments. Because of a lack of information, we cannot describe the use of ballot measures immediately before and after Proposition 13.11 Our sample allows us to illustrate changes in the relative importance of the more recent restrictions, including the initial responses of local governments to the implementation of a new limit (i.e., Proposition 218) and the relaxing of an existing limit (Proposition 39). We have information on 1,462 tax measures and 1,184 bond measures between 1986 and 2000. Forty-six percent of our election data apply to school districts, 27 percent apply to cities, 8 percent apply to counties, and the rest apply to special districts.12 We find that use of tax measures has increased since 1996, not surprisingly given the passage of Proposition 218 and the conclusion of the Proposition 62 court challenges. Because of the changing environment for school districts following passage of Proposition 39 in 2000, we have also included some preliminary information on school bond elections in 2001 and 2002. Before examining specific election results, we next compare patterns in aggregate finances in California to those in the rest of the country. California and U.S. Local Government Finances Thus far, we have discussed the changing constraints placed on local governments and how the state has responded. Part of the aftermath of the Serrano decision and Proposition 13 was a shift in the sources of revenues available. Before examining differences across local governments in California, it is worth looking at whether these changes ____________ 11Cain et al. (1996) found that the use of ballot propositions to fund libraries was very uncommon before 1986. 12Note that limitations on election data mean that we may be missing ballot measures for certain governments. 13 led to differences in the overall level of local government revenues. Has California local finance diverged from that found in the rest of the country? Have spending levels declined? We examine overall local government finance patterns by comparing aggregate local government revenues to revenue levels in the rest of the country. To do this, we use information from the U.S. Bureau of the Census, Census of Governments, for 1972 to 1997.13 We aggregate local revenues to the state level and present figures in real (2000) dollars per capita. California’s local governments spent more on average than most states but less than New York—which is similar to California in terms of wealth, size, and population diversity (Figure 2.1).14 Real local revenues were about $3,000 per person in California in 1972. This level fell following the passage of Proposition 13, but revenue levels fell in New York and the rest of the country as well. Revenues increased after 1982 in California, New York, and the rest of the United States. In Figure 2.2, we compare own-source revenues; that is, we subtract revenues that are raised from state and federally controlled tax sources and then transferred to local governments. In 1972, revenue levels from California’s own sources were similar to those in New York and were much larger than the average in the rest of the country. Following Proposition 13, own-source revenues fell dramatically in California. By 1997, approximately 45 percent of California’s local government funds came from another level of government. Much of this change in state control is due to increased state funds for school districts and counties. We further examine this change in funding by comparing per capita total revenues for California local governments to those in the rest of the country by type of government entity (Table 2.2). Note that although California’s total local revenue levels are higher than those in the rest of the United States, municipal revenues are lower and county and special district revenues are much ____________ 13For more information about Census of Governments data, see Appendix B. 14We have also examined similar figures for other states that may be thought comparable to California, including Texas, Arizona, and Oregon, and find that they have spending patterns similar to the U.S. average. 14 Revenue dollars (2000) 5,500 5,000 4,500 4,000 3,500 3,000 2,500 2,000 1,500 1,000 500 0 1972 1977 New York California United States excluding California 1982 1987 1992 1997 Figure 2.1—Real Per Capita General Revenue, All Local Governments 4,000 3,500 3,000 New York California United States excluding California 2,500 2,000 1,500 1,000 500 0 1972 1977 1982 1987 1992 1997 Figure 2.2—Real Per Capita Own-Source General Revenue, All Local Governments Revenue dollars (2000) 15 Table 2.2 Per Capita Revenue in California and the Rest of the United States Type of Government California All local governments Counties Cities School districts Special districts Excluding school districts 1972 1977 1982 1987 1992 1997 General Revenue 3,119 1,155 635 1,148 182 1,972 3,362 2,922 1,119 927 756 719 1,239 968 248 308 2,123 1,954 3,428 1,099 848 1,079 401 2,349 3,820 1,311 913 1,177 420 2,643 3,820 1,212 944 1,192 472 2,628 United States excluding California All local governments Counties Cities School districts Special districts Excluding school districts 2,068 406 807 757 98 1,311 2,280 2,187 481 478 894 803 779 732 125 173 1,501 1,455 Own-Source General Revenue California All local governments Counties Cities School districts Special districts Excluding school districts 2,226 638 650 705 234 1,521 1,957 1,422 560 378 523 543 680 287 194 214 1,277 1,135 2,554 579 918 845 212 1,709 1,767 478 683 293 314 1,474 2,802 653 972 951 226 1,851 1,966 543 752 352 319 1,614 2,991 713 1,012 1,020 246 1,972 1,908 435 755 419 299 1,489 United States excluding California All local governments Counties Cities School districts Special districts Excluding school districts 1,231 238 527 409 57 822 1,297 1,280 275 296 552 520 388 352 82 112 910 928 SOURCE: U.S. Bureau of the Census (1972–1997) 1,585 393 643 402 147 1,183 1,756 448 689 463 156 1,293 1,853 490 721 473 169 1,380 higher. Throughout this period, California has relied more on special district governments than have other states. California’s local governments are following a different trend from that of the rest of the country in terms of raising local revenues. In the rest of the country, overall own-source revenues increased from 57 percent of funds to 62 percent of funds from 1977 to 1997. In California the trend is reversed, with own-source funds declining from 16 58 percent to 50 percent. These patterns are even more dramatic when examined by specific level of government. County own-source funds declined from about half of funds in 1977 to 36 percent in 1997; in the rest of the United States, those funds increased from 57 percent to almost 70 percent of funds. School districts in both the rest of the country and in California are increasingly under state control, reflecting the wave of school finance equalization cases that have occurred in a majority of states. However, California’s changes are even larger than those found elsewhere. California school districts went from having 55 percent of funds from local sources to having a little over one-third, whereas ownsource revenues in school districts in other states fell only from 54 to 46 percent. Because property tax funds are counted as own-source revenues by the Census of Governments, these changes actually understate the growing reliance of local governments on state sources for finances. Thus, over the past 30 years, school districts and county governments in California have become increasingly reliant on state funds. This has led to a loss of autonomy in fiscal decisionmaking for these levels of governments. California has also become more dependent on special districts to provide local services—with revenues controlled by special districts growing from 7 to 12 percent of local government finances. 17 3. School District Elections and Their Effect on Revenues We saw in Chapter 2 that school districts primarily used the ballot box to gain approval for bond measures to finance school building or modernization programs. Of the 1,168 ballot measures proposed by school districts between 1986 and 2000, 947, or 81 percent, were bond measures. This pattern is very different from other local governments, which depend more on tax measures. This difference in usage is partly due to school districts’ lack of direct control in deciding the level of current fund expenditures in the aftermath of the Serrano lawsuits. In this chapter, we examine how school districts have responded to the lowered voter requirements following the passage of Proposition 39. We then look into what leads school districts to the ballot box and explore differences in capital funding levels across school districts that were and were not successful. Finally, we turn our attention to tax elections and explore the characteristics of school districts that have parcel tax elections and how passage of parcel taxes affects current expenditure levels. School District Bond Elections Over the 1986–2000 period, there were 947 bond elections across the 1,058 school districts. All types of school districts proposed bond measures, with the most activity on a per district basis (approximately 1.3 elections per district) occurring in unified and secondary school districts and very few (0.36 elections per district) occurring in community college districts. Passage rates were highest for elementary school districts and were lowest for community college districts (Table 3.1). The number of school district bond elections increased over time, especially in the later years (Figure 3.1). Before Proposition 39, the largest number of bond elections placed on a single ballot was 48 in November 1997. This activity was partly due to the availability of 19 Table 3.1 Distribution of Bond Measures Proposed and Passed by School Districts, by Type, 1986–2000 Type of District Unified Elementary school High school Community college No. of Districts 325 570 92 71 Average Enrollment 12,706 2,116 5,933 19,732 No. of Measures Proposed 431 363 127 26 Passage Rate (%) 50 62 50 42 Total or average 1,058 6,883 947 54 NOTES: The number of districts and total enrollment are from the California Department of Education, 1999–2000. Community college district enrollment includes part-time enrollment. Number of measures 120 100 80 60 40 20 0 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 NOTES: Each period is one-third of a year. The year labels correspond to the third period, including the November general election. Figure 3.1—Number of Bond Measures Proposed by School Districts, 1986–2002 $3 billion in state matching funds that were approved in the 1996 statewide election with the passage of Proposition 203. The presence of additional state money could have acted as an incentive for local districts 20 Passage rate, % to place bond measures on the ballot, as districts need local funds to be eligible for state funds. Bond measures are also more likely to appear on general election ballots than at other periods during the year. Passage rates increased over time (Figure 3.2). Note that this increase began in the late 1990s, even before the passage of Proposition 39, which lowered the majority required for approval from two-thirds to 55 percent. March 1996 was the election with the highest passage rates (86 percent) before the passage of Proposition 39, but this may be because only seven elections were on the ballot. This passage level was reached and surpassed in the aftermath of Proposition 39, when the lower vote requirement was in place. 100 90 80 70 60 50 40 30 20 10 0 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 NOTE: Each period is one-third of a year. The year labels correspond to the third period, including the November general election. Figure 3.2—Passage Rate of Bond Measures Proposed by School Districts, 1986–2002 Bond Measures Since the Passage of Proposition 39 We next examine in more detail the results of elections that occurred after passage of Proposition 39. In March 2001, eight school districts had elections and five bond measures were passed, but only one school district did not reach the previous threshold of a two-thirds majority. Of 21 the three bond measures that failed, two received more than 55 percent of the vote. Because there were no other general elections occurring in the same jurisdiction, they were ineligible for the lowered vote requirement.1 In November 2001, 32 bond measures were proposed and 29 were approved. This increased passage rate is partly due to the lower threshold for passage. If a two-thirds majority had been in place, six of these bond measures would have failed. In March 2002, the effect of the lower passage requirement was even more dramatic—76 bond measures were proposed and 67 passed, the vast majority of which (42 of the 67 that passed) would have failed if a two-thirds vote had been needed (Table 3.2). There were 103 bond measures on the November 2002 ballot of which 84 passed.2 The other striking result following passage of Proposition 39 was a dramatic increase in local ballot measures by community college districts. Community college districts proposed five bond measures in November 2001 and 14 in March 2002, with four of them passing in November and 12 passing in March. Sixteen bond measures for community college Table 3.2 Number of Bond Measures Proposed and Passed by School Districts Since Passage of Proposition 39 No. of No. of Measures Measures Over TwoProposed Passed Thirds All School Districts March 2001 85 November 2001 32 29 March 2002 76 67 November 2002 103 84 Community College Districts 4 23 25 41 March 2001 November 2001 March 2002 November 2002 0 00 5 43 14 12 3 16 15 4 ____________ 1The lower requirement is applicable only if another election is already scheduled. 2Information on the November 2002 ballot is preliminary and we would like to thank Deborah Finestone of the Bond Buyer and Patti Herrera of the Coalition for Adequate School Housing for providing us with a list of these measures. 22 district funding were on the November 2002 ballot. Before 2001, community college districts had proposed only 26 bonds of which 11 had passed. Regional Patterns in Bond Elections We next examine differences in proposal and passage rates across regions in the state.3 The Central Valley area and the southern region of the state proposed more bond measures than the other regions (Table 3.3). However, the San Francisco Bay Area, with 163 school districts and 197 bond elections, had the highest average number of measures Table 3.3 Number of Bond Measures Proposed and Passed, by Region, 1986–2002 Region Northern Bay Area Valley Coastal Southern No. of Districts 240 163 262 99 223 1986–2000 No. of Measures Passage Proposed Rate (%) 124 38 197 75 242 45 93 55 265 57 2001–2002 No. of Measures Passage Proposed Rate (%) 24 75 42 93 48 83 16 81 54 81 Total or average 987 921 55 184 84 NOTE: The following counties are contained in each regional grouping: Northern—Alpine, Amador, Butte, Colusa, Del Norte, El Dorado, Glenn, Humboldt, Lake, Lassen, Mendocino, Modoc, Nevada, Placer, Plumas, Shasta, Sierra, Siskiyou, Sutter, Tehama, Trinity, and Yuba; Bay Area—Alameda, Contra Costa, Marin, Napa, San Francisco, San Mateo, Santa Clara, Solano, and Sonoma; Valley—Calaveras, Fresno, Inyo, Kern, Kings, Madera, Mariposa, Merced, Mono, Sacramento, San Joaquin, Stanislaus, Tulare, Tuolumne, and Yolo; Coastal—Monterey, San Benito, San Luis Obispo, Santa Barbara, Santa Cruz, and Ventura; Southern— Imperial, Los Angeles, Orange, Riverside, San Bernardino, and San Diego. ____________ 3For the remainder of the analysis, we exclude community college districts from our analyses. This is partly due to the small number of ballot measures these districts used and also to the different population they served. 23 proposed—1.2 bond measures per district. The Bay Area also had the highest passage rate—75 percent before 2001 and 93 percent after the passage of Proposition 39. School districts in the northern region had the lowest bond proposal and passage rate, with 240 districts proposing only 124 bond measures, of which only 38 percent passed. After Proposition 39, passage rates increased in all regions, most notably in the northern region and the Central Valley. The patterns we find across regions resemble those within regions if we look at the prevalence of proposing elections in different counties. We find that most elections occurred in Los Angeles County (98), San Diego County (52), and other Southern California counties (Figure 3.3). This partly reflects the higher number of school districts found in 0 1–9 10–24 25–44 45–98 Figure 3.3—Number of Bond Measures Proposed by School Districts, 1986–2000 24 counties in Southern California.4 A large number of elections also occurred in Santa Clara County (45) and many other Bay Area counties. Passage rates were high in most Bay Area counties (see Figure 3.4). Mono, Plumas, and San Francisco Counties had a 100 percent passage rate, although they had very few elections because of having only one or two school districts per county. Los Angeles County had the most bond elections (18) followed by San Diego, Sacramento, and Santa Clara. The eight elections placed on the ballot in Orange County over the last two years constituted more than half the number placed on the ballot over the prior 14 years. No bond measures 0–25 26–50 51–75 76–100 Figure 3.4—Passage Rate of Bond Measures Proposed by School Districts, 1986–2000 ____________ 4The number of school districts in each county, the number of bond elections, and passage rates can be found in Appendix Table C.1. The maps exclude elections held by community college districts. 25 Passage rates also increased dramatically in virtually all the counties that had an election (see Appendix Table C.1). Distribution of Bond Measures Across School Districts Up to this point, we have examined patterns in bond elections in California, but we have not differentiated between instances where a given school district had multiple elections or many school districts each had a single election. We now turn our attention to the frequency of elections across school districts between 1986 and 2000. Of the 987 non–community college districts, about half (546) held at least one election. Of these, 58 percent of school districts held one election, 24 percent held two, 11 percent held three, and only 6 percent held four or more elections (Table 3.4). We observe a decline in passage rates as the number of elections increases. Thus, school districts appear to return to the ballot box if they were originally unsuccessful in gaining voter permission to issue a bond measure. For school districts that went to the ballot box up to four times, the amount raised was fairly constant and averaged between $5,000 and $7,000 per pupil. Thus, it seems that school districts that wanted to raise a certain amount of money returned to the ballot box until it was raised. If in this earlier period the passage rate for school construction measures had been 55 percent (the required supermajority under Table 3.4 Distribution of Bond Measures Proposed by School Districts, 1986–2000 No. of Measures Proposed 0 1 2 3 4 5 6+ Total or average No. of Districts 441 319 131 62 22 8 4 987 Passage Rate (%) 81 52 34 34 25 19 66 Average $ per Student Proposed Passed 00 7,166 5,317 13,525 6,562 16,541 5,130 17,249 4,906 53,126 14,393 25,394 4,908 10,977 5,708 26 Proposition 39) rather than two-thirds, 89 percent of bond measures would have passed. However, if the vote requirement had been lower, there would have been a different makeup of elections, as school districts that were successful on their first ballot would not necessarily have returned to the ballot box. Therefore, the amount of money raised would have probably increased although not by the amount of all bond measures proposed. Of the 169 non–community college school districts that have proposed a bond measure since the passage of Proposition 39, 46 did not propose a bond measure in the 1986–2000 period, 52 proposed at least one bond measure before but never successfully passed a bond, and 71 districts were able to pass a bond measure under the two-thirds requirement. Thus, it seems that lowering the vote requirement increased the successful usage of the ballot box by school districts. About 22 percent of the 546 school districts that had proposed at least one bond measure were ultimately unsuccessful as of 2000 (Table 3.5). Thirty-six percent of school districts (or 358) had one successful bond measure, 62 school districts had two, six had three measures pass, and only one school district (San Francisco Unified School District) passed four bond measures. On average, school districts that passed two or three bond measures had a higher amount of bond funds per student. Surprisingly, San Francisco Unified School District, which passed four Table 3.5 Distribution of Bond Measures Passed by School Districts, 1986–2000 No. of Measures Passed 0 1 2 3 4+ Total or average No. of Districts 560 358 62 6 1 Passage Rate (%) 84 84 85 100 Average $ per Student Proposed Passed 2,300 0 9,986 6,613 15,909 10,960 13,956 10,714 6,286 6,286 987 66 10,977 5,708 27 measures, raised slightly less than $6,300—less than the average amount raised by school districts that passed only one measure. Determinants of School District Bond Elections and Capital Expenditures We turn now to the question of which characteristics seem to lead school districts to the ballot box. Do these characteristics reflect differences among districts facing growing and shrinking enrollments? Do they reflect differences in the income levels or property values across districts? And how does the use of the ballot box influence overall levels of capital financing? We limit our sample to districts that can be linked to demographic data, and we analyze unified school districts separately because they serve the vast majority of California’s students and are much larger. Of the 726 school districts for which we have demographic information as of 2000, 295 never proposed a bond measure, 78 proposed but never passed a bond measure, and 353—almost half of all school districts—passed a bond measure. Thus, the percentage of school districts that were successful in passing new bond measures is slightly higher in the sample of schools remaining. This result is not surprising, as the omitted school districts are mainly in rural areas that are not facing enrollment growth.5 We first examine factors that may have led to differences in school districts proposing or passing new measures. That is, we examine demographic differences among school districts that did not propose a ballot measure, those that proposed but did not pass at least one measure, and those that were successful in passing at least one new bond measure. We would expect districts with growing student populations to require more facilities financing, so we examine the effect of student enrollment sizes and enrollment growth on the decision to attempt to pass a bond measure. Because limits on school district debt are based on assessed ____________ 5Information on school district demographics is from the U.S. Department of Education (1990) based on 1990 Census information. Unfortunately, this information is not available for school districts in Butte, El Dorado, Humboldt, Madera, Monterey, Napa, Santa Barbara, or Siskiyou Counties. We also combine information on districts that merged over this period. We are left with 726 districts for the remainder of our analysis. 28 value (1.25 percent of assessed value for elementary or secondary districts and 2.5 percent for unified districts), there is a direct relationship between assessed value and the maximum amount of money that can be raised. We would also expect school districts with a higher percentage of older voters to be less likely to pass new school bonds, as they would not directly benefit from the new or improved facilities.6 We also examine how differences in family income, the racial makeup of the population, and the percentage of homeowners in a district affect the prospects of proposing or passing a bond measure. We find that larger school districts were more likely to have a bond election and that, on average, those that were successful were very large. School districts that did not have any bond elections had student populations of about 2,300 in 1999–2000, those that had a bond election but were unsuccessful had an average of 6,900 students, and successful school districts had about 10,200 students. Thus, higher enrollment increases the probability of having a bond election. See Table 3.6 for the average level of enrollment and the other descriptive characteristics of these three sets of school districts. School districts that were successful at passing a bond measure had higher enrollment growth than both districts that never proposed an election and those that failed to ever pass a bond measure. School districts that were never successful in passing a bond measure had lower assessed values, whereas successful school districts had lower assessed value per student than districts that never proposed a bond measure but had higher assessed value than those that failed to pass a bond measure. Thus, assessed value seems to affect school districts’ ability to pass a bond measure. Average household income also differs across the three sets of districts. Income was highest for districts that successfully passed a bond measure and lowest for districts that proposed but did not pass a bond. School districts that held bond elections (whether successful or not) had a higher ____________ 6These households may benefit by improved school facilities indirectly if these improvements lead to higher home prices. For a discussion of house price capitalization and school quality, see Sonstelie, Brunner, and Ardon (2000). 29 Table 3.6 Demographic Characteristics of School Districts, by Bond Measure Experience Did Not Proposed and Proposed Overall Propose Did Not Pass and Passed All School Districts Average daily attendance 6,653 2,339 6,909 10,202 % growth in average daily attendance, 125.2 119.6 126.0 129.7 1989–1998 Assessed value per student, $ 654,424 746,373 504,179 610,782 Mean household income, $ 44,661 42,423 37,705 48,068 % over age 65 11.3 12.0 11.5 10.7 % nonwhite 36.8 32.5 39.3 40.0 % homeowner 64.0 64.9 67.0 62.6 No. of districts 726 295 78 353 Unified School Districts Average daily attendance 13,478 5,812 8,422 17,716 % growth in average daily attendance, 125.4 116.6 125.8 128.5 1989–1998 Assessed value per student, $ 416,481 517,473 257,085 425,880 Mean household income, $ 44,429 38,722 37,219 48,578 % over age 65 11.3 12.8 11.9 10.6 % nonwhite 39.3 34.6 44.1 39.6 % homeowner 63.0 62.9 66.1 62.1 No. of districts 246 54 43 149 percentage of nonwhite students in the district. All other demographic characteristics were similar across the three groups of districts. The overall numbers may mask differences in behavior among unified school districts and elementary and high school districts. Thus, we now turn our attention to unified school districts in California. Of the 246 unified districts in our sample, 54 never proposed a school bond measure, 43 proposed at least one measure but never passed one, and 149 passed at least one measure. We find that average attendance levels were larger in unified districts for all three groupings. Unified school districts that had bond elections tended to be larger, and those that were successful at passing new measures were larger still than those districts that did not propose or were not successful in passing a bond measure. Successful districts also had higher family incomes than districts that did 30 not propose or pass any bond measures. Districts that proposed bond measures were faster-growing and had a higher average percentage of nonwhite student enrollment than those that did not propose a bond measure. Unified school districts that were successful had higher assessed value than those that were unsuccessful but lower assessed value than those that never proposed a measure. Demographic characteristics of unified school districts can be found in the lower panel of Table 3.6. Does holding an election affect overall capital revenues? School districts that did not hold a successful bond election may have been able to raise funds using developer fees or state aid. Thus, we now turn our attention to how much money was raised by each group of school districts for capital expenditures. If we compare capital revenues per student spent in the 1992–2000 period, we find that school districts that passed a bond measure between 1986 and 2000 had higher bond revenues and also had substantively higher total per pupil capital revenues. Figure 3.5 shows average per pupil bond revenues and overall capital revenues by election success. School districts without a successful bond election spent about $3,000 per student on capital projects, whereas school districts that were successful spent more than double that amount, $6,600. Not surprisingly, very little funding came from bond money in school districts that did not have at least one successful ballot measure. The small amount of bond funding listed for districts without an election was from the 1 percent of these districts that had a bond election prior to our sample period. School districts that were unsuccessful at passing a local bond did receive a higher amount of state aid on average (Table 3.7). Other local sources included revenue from Developer Fees and Certificates of Participation (COPs).7 School districts that had successful bond elections also were successful in raising other local funds and had higher levels of revenues from fees and COPs. It may be that the underlying characteristics that lead voters to pass new bond measures (such as increased enrollment growth) will also lead to support for other local funds. ____________ 7See Brunner and Rueben (2001) for a discussion of overall school facility funds. 31 Revenue dollars (2000) 7,000 6,000 5,000 4,000 Average district Did not propose Proposed and did not pass Proposed and passed 3,000 2,000 1,000 0 Capital revenue Bond revenue Figure 3.5—Average Total Capital Revenue and Bond Revenue per Student, 1992–2000 Table 3.7 School District Per Pupil Capital Revenue, by Bond Measure Experience Did Not Overall Propose All School Districts Total capital revenues per student Bond revenues per student State funds per student Fees per student COPs per student 4,705 1,803 1,273 640 132 2,852 116 1,304 493 64 Unified School Districts Total capital revenues per student Bond revenues per student State funds per student Fees per student COPs per student 4,397 1,780 1,087 575 171 2,621 186 842 373 169 NOTE: Amounts are in constant year 2000 dollars. Proposed and Proposed Did Not Pass and Passed 3,072 0 1,532 608 161 6,615 3,607 1,190 769 182 2,691 0 1,542 506 116 5,534 2,865 1,045 669 187 For unified districts, average funding levels for each group were slightly lower than the average for all school districts. However, as with average numbers for all districts, funding levels for unified districts that 32 held successful bond elections were, on average, twice as high as for those that did not, and the largest increase in spending came from bond funds (Table 3.7, bottom panel). The results presented thus far show average differences in the three groups of school districts but do not make clear which differences are important in the proposal or passage process and how passing a bond measure affects total capital spending. To examine how these different characteristics interact and cumulatively influence the decision to propose bond measures and the probability that voters will pass them, we use regression analysis. Regression analysis allows us to disentangle relationships among variables and to estimate how much of the difference seen across regions is actually driven by differences in assessed values and enrollment growth. Using these estimates allows us to predict how proposal rates would differ if we were to change only one characteristic of a school district.8 We first examine which factors influence the decision to propose a bond measure. (These results for all school districts and unified districts only can be found in the first two columns of Appendix Table C.2.) We find that after controlling for demographic characteristics, the probability of proposing a bond measure for an average district is 52 percent. In Table 3.8, we provide information on the influence of different school district characteristics by estimating the change in probabilities of proposing and passing a bond measure as district characteristics change.9 We find that elementary school districts are less likely to propose a bond measure than are either unified or high school districts (41 percent for elementary school districts, 66 percent for unified districts, and 64 percent for high school districts). We also find that larger enrollments ____________ 8We follow a similar estimation strategy to that used by Brokaw, Gale, and Merz (2001) in modeling voter elections. For a more complex modeling strategy, see Balsdon, Brunner, and Rueben (2002), who use a three-equation model to examine the decision to propose a bond measure, passage rates, and the amount passed, controlling for sample selection for unified districts. 9For our estimates, we calculate passage rates for an “average” school district that has characteristics equivalent to those of the median school district and compare the effect of changing a district characteristic to that found at the 25th or 75th percentile. The values of these exercises can be found in Appendix Table C.3. 33 Table 3.8 Estimated Change in Probability of Proposing and Passing Bond Measures Average district Unified district Elementary school district High school district Average daily attendance Average daily attendance growth, 1989–1998 Assessed value per student Mean household income Percentage homeowners Probability of Proposing 52.3 66.4 41.2 64.4 Low High 49.4 60.2 51.2 53.4 Probability of Passing 42.3 48.9 36.3 54.2 Low High 40.5 47.4 41.2 43.4 Probability of Passing If Proposed 81.1 71.9 85.7 80.9 Low High 81.1 81.2 80.2 82.0 52.5 51.9 51.5 53.3 50.8 53.8 42.8 41.3 81.4 80.5 39.9 45.5 72.0 89.8 44.7 39.9 88.7 70.7 NOTES: Low and high probabilities correspond to the 25th and 75th percentiles, respectively. An average district corresponds to a district with median characteristics. See Appendix Table C.3 for the corresponding values of the variables. increase the probability of proposing a bond measure. For a district with average enrollment, or 2,211 students, the probability of proposing a bond measure is 52 percent, whereas for a district with a high enrollment, or 7,039 students, the estimated probability of proposing a bond measure would increase by 8 percentage points to 60 percent. Enrollment growth also has a statistically significant and positive effect on the probability of proposing or passing a bond measure, although the changes in probability are small. Our results are weaker when we examine only unified school districts but they follow the same patterns. We next examine the probability of passing a bond measure across school districts. We find that elementary school districts are again least likely to pass new bonds (36 percent), whereas high school districts, which have nearly the same estimated probability of proposing a measure as unified districts, have a higher probability of passing a bond measure overall (54 versus 49 percent). Higher enrollments also increase the probability of passing bond measures, as does higher household income. Moving from the median average daily attendance to a school with 34 relatively high enrollment increases the probability of passing a measure from 42 to 47 percent. Changing the average household income in a district from the state average ($40,754) to a lower level ($32,712) also diminishes the chances of passing a measure, from 42 to 40 percent. School districts with a higher percentage of homeowners are less likely to pass a new bond measure—possibly because they directly bear the burden of paying back the bond. If the percentage of homeowners in a district changes from 73 percent to 57 percent, the probability of passing a measure increases 5 percentage points (from 40 to 45 percent). If we limit our regressions to unified school districts, we find similar results. Although elementary school districts are less likely than unified and high school districts to propose bond measures, their measures are more likely to pass once on the ballot. If an elementary school district places at least one measure on a ballot, its estimated chance of passing a bond is 86 percent, whereas a unified district’s average passage rate conditional on proposing is 72 percent and a high school district passage rate is 81 percent. The lower passage rate for unified districts (as compared to elementary and high school districts) may have to do with the larger size and increased number of schools in the district. Finally, we use regression analysis to explore how spending varies across each group of school districts by examining demand for capital expenditures. These results are found in Appendix Table C.4. We follow the methodology used in Bergstrom, Rubinfeld, and Shapiro (1982) and Borcherding and Deacon (1972). We focus on spending levels in the period between 1992 and 2000, and we collapse spending at any point in that period into one aggregate figure.10 State matching funds are primarily based on enrollment growth; thus, we would expect to see a positive relationship between spending and enrollment numbers and growth rates. This is indeed the case. A district with an average daily attendance of 2,211 has estimated total capital revenues of $2,004 per student, whereas a district with larger enrollment (7,039) has estimated revenues of $2,538 per student. We also find a positive relationship between spending levels and assessed value per student. The ____________ 10For a more technical discussion of school bond elections in unified districts that includes variation over time see Balsdon, Brunner, and Rueben (2002). 35 assessed value per student varies greatly across districts; an average district’s value is about $400,000, whereas a low assessed value district has a value of about $255,000. Lowering the assessed value from $400,000 to $255,000 would lead to a 15 percent decline in capital spending per student, from $2,004 to $1,711. Economic theory predicts that districts with higher assessed value are able to raise more funds because a given increase in property tax rates will raise more money in a district with a higher level of assessed value than in a district with less property wealth. Other household demographics do not significantly affect spending levels, although high school districts receive lower funds on a per pupil basis ($1,415) than do elementary ($2,206) or unified ($1,904) school districts. Appendix Table C.4 also presents results for unified school districts only, and we find very similar patterns to the sample as a whole. After controlling for other district characteristics, we still find regional differences in capital revenues. Bay Area districts raise $3,500 on average compared to $2,472 for coastal districts and about $2,000 per pupil for districts in other regions. School District Parcel Tax Elections Tax elections make up about 20 percent of all school district measures. The only tax measures proposed by school districts are parcel taxes. The small reliance on tax measures is partly due to revenue limits placed on school districts and the relatively small amount of money per pupil raised by a parcel tax.11 Table 3.9 presents information on tax measure elections for the different types of school districts. Elementary school districts are the most likely to propose a parcel tax and have the highest passage rate. Only one community college district (Los Angeles Community College District) proposed a parcel tax during this period. Parcel taxes differ from property taxes in that they are not based on the assessed value of property but rather on a set amount of money per structure—sometimes differing by type of structure (residential, ____________ 11See Sonstelie and Richardson (2001, Chapter 9), for more information on the role that parcel taxes play in current school district finances. 36 Table 3.9 Distribution of Parcel Tax Measures Proposed and Passed by School Districts, by Type, 1986–2000 Type of District Unified Elementary school High school Community college No. of Districts 325 570 92 71 Total Enrollment 12,706 2,116 5,933 19732 No. of Measures Proposed 86 117 18 1 Passage Rate (%) 44 63 56 0 Total or average 1,058 6,883 222 55 NOTES: Number of districts and total enrollment are from the California Department of Eduction, 1999–2000. Community college district enrollment includes part-time enrollment. commercial, or multiunit).12 School districts typically proposed taxes between $20 and $200 per parcel. School district parcel taxes were usually imposed with specific time periods for collections, usually around 4–5 years, although a few were proposed for 10 or more years, and two were proposed without expiration dates. Berkeley Unified School District proposed parcel taxes over this period that specified an amount of money per square foot of space. It was also the only district in our sample to propose parcel taxes with different amounts of money collected from residential and commercial space. Thus, the majority of school districts that proposed parcel taxes proposed a set amount per structure for a given number of years. In the next chapter, we examine city parcel tax measures and find a more varied pattern of usage. Far fewer tax measures were proposed than bond measures, averaging a little less than 20 measures per year. The number of measures proposed peaked in 1991, when 33 measures were proposed, but that number has dropped more recently (Figure 3.6). The state was facing budget difficulties in the early 1990s and was not increasing funding for school districts. Passage rates increased throughout this period, but this may reflect the decline in the number of ballot measures proposed (Figure 3.7). ____________ 12In contrast, if a bond measure is passed it leads to a temporary increase in property tax rates. 37 Number of measures 40 35 30 25 20 15 10 5 0 1986 1988 1990 1992 1994 1996 1998 2000 2002 Figure 3.6—Number of Parcel Tax Measures Proposed by School Districts, 1986–2002 100 90 80 70 60 50 40 30 20 10 0 1986 1988 1990 1992 1994 1996 1998 2000 2002 Figure 3.7—Passage Rate of Parcel Tax Measures Proposed by School Districts, 1986–2002 Passage rate, % 38 Regional Patterns in Parcel Tax Elections The vast majority of parcel taxes, 68 percent, were proposed in the Bay Area, where passage rates were also the highest (Table 3.10). As with bond measures, the northern region proposed the fewest measures per district. Passage rates were lower than those of bonds in all regions, with the coastal region having the lowest passage rate, 8 percent. If we look across counties, we again see that Bay Area counties, especially Marin County with 48 measures, proposed the most parcel taxes (Figure 3.8).13 School districts in Sonoma, Santa Clara, and Los Angeles Counties placed 24 measures each during this time period, although the Los Angeles figure partly reflects the higher number of school districts in the county. In 32 counties, no school districts proposed a parcel tax. Yolo County passed all four measures that were proposed, although these results are due to elections held only in the Davis School District. Marin, with the highest number of measures proposed, had the second-highest passage rate, 85 percent, passing 41 of the 48 measures proposed. Table 3.10 Distribution of Parcel Tax Measures Proposed and Passed by School Districts, by Region, 1986–2000 Region Northern Bay Area Valley Coastal Southern No. of Districts 240 163 262 99 223 No. of Measures Proposed 9 151 17 13 31 Passage Rate (%) 44 68 41 8 26 Total or average 987 221 55 ____________ 13Appendix Table C.5 includes county-level statistics for Figure 3.8. 39 0 1–4 5–9 10–19 20–48 Figure 3.8—Number of Parcel Tax Measures, by School District, 1986–2000 Distribution of Tax Measures Across School Districts Unlike bond measures, parcel taxes were proposed by a relatively small group of districts, with 88 percent of districts never proposing any tax measures. About half the school districts that proposed tax measures proposed only a single one; one-quarter proposed two measures, and one-quarter proposed three or more measures (Table 3.11). Only 55 school districts successfully passed a parcel tax. Passage rates increased as the number of measures proposed increased—so proposing and voting behavior seem very different from that found for bond measures. For bond measures, the majority of districts that had elections had a single successful election, but for parcel tax measures, districts that had elections often passed multiple measures over the 1986– 40 Table 3.11 Distribution of Parcel Tax Measures Proposed by School Districts, 1986–2000 No. of Measures Proposed 0 1 2 3 4 5 Total or average No. of Districts 871 57 29 16 12 2 Passage Rate (%) 25 36 79 85 80 987 42 2000 period. This pattern usually occurred because districts would propose a new parcel tax to replace an expiring tax (Table 3.12). By 2000, only five districts had two concurrent parcel taxes in place at the same time, although for most, the total amount accumulated was still less than $200. The only districts with parcel taxes higher than $200 per parcel in 2000 were Kentfield ($295), Lagunitas (two parcel taxes raising $145 and $165), Loma Prieta (two $150 parcel taxes), Los Gatos ($250), Mill Valley ($275), Piedmont ($497 and $130 parcel taxes), and Ross ($495). Table 3.12 Distribution of Parcel Tax Measures Passed by School Districts, 1986–2000 No. of Measures Passed 0 1 2 3 4+ Total or average No. of Districts 932 18 14 17 6 987 Passage Rate (%) 88 88 87 100 42 41 Determinants of School District Tax Elections and Current Revenues In the previous section, we saw that relatively few school districts propose parcel taxes and that few funds are raised this way. We now examine whether these school districts look different from school districts that never proposed a parcel tax and those that proposed but never passed a parcel tax.14 As was the case for bond measures, we have demographic information on only a limited set of school districts, 726. Of these districts, 617, or 85 percent, never proposed a tax measure, 54 proposed but did not pass a tax measure, and 55 passed at least one tax measure. Table 3.13 presents information on the demographic characteristics of all school districts and unified school districts by parcel tax usage. School districts that passed a tax measure were smaller than other districts. Student populations of school districts with parcel tax measures were on average about 3,800 as compared to 6,800 students on average in districts that did not propose elections and 7,900 students in districts that were unsuccessful. Assessed value is much higher on a per pupil basis in those districts that passed at least one tax measure, which partly reflects the smaller student populations in these districts. Mean household income was also much higher for districts that passed a parcel tax. They also had fewer nonwhite students than did districts that did not propose parcel tax measures. We find similar patterns if we restrict our sample to unified school districts, although in this limited sample it is striking how similar unified school districts that proposed and did not pass tax measures are to those that were successful at passing ballot measures. That is, for unified districts, only districts with high property values and high income seem to propose tax measures. ____________ 14We have also examined the differences across school districts that have and have not proposed a parcel tax using a regression framework. We find differences across types of districts, but our results lack statistical significance because of the limited number of school districts that have passed parcel taxes. We find that elections are more prevalent in the Bay Area and school districts with higher-income households and fewer nonwhite households are both more likely to propose and pass a parcel tax. These regressions are available from the authors upon request. 42 Table 3.13 Demographic Characteristics of School Districts, by Parcel Tax Experience, 1986–2000 Characteristic Did Not Proposed and Proposed Overall Propose Did Not Pass and Passed All School Districts Average daily attendance 6,653 % growth in average daily attendance, 125.2 1989–1998 Assessed value per student, $ 654,424 Mean household income, $ 44,661 % over age 65 11.3 % nonwhite 36.8 % homeowner 64.0 No. of districts 726 6,796 126.1 614,467 41,318 11.1 39.2 63.6 617 7,918 119.9 3,802 121.0 729,596 1,028,874 56,172 70,859 11.5 13.4 29.5 17.4 63.8 68.3 54 55 Unified School Districts Average daily attendance 13,478 % growth in average daily attendance, 123.8 1989–1998 Assessed value per student, $ 416,481 Mean household income, $ 44,429 % over age 65 11.3 % nonwhite 39.3 % homeowner 63.0 No. of districts 246 14,210 124.8 389,930 41,523 11.3 42.5 63.2 204 11,116 119.0 7,773 120.0 580,401 60,091 11.5 23.5 62.7 27 482,520 55,766 11.6 25.1 60.8 15 If we specifically examine regional patterns in proposing or passing tax measures, we find that school districts in the Bay Area are much more likely to propose and pass at least one tax measure. Forty-seven percent of Bay Area school districts proposed a parcel tax and 30 percent successfully passed at least one. School districts in other regions of the state had much lower proposal and passage rates. Less than 3 percent of districts in other regions passed any parcel taxes. Parcel tax revenues are concentrated in the San Francisco Bay Area in high-income and high-assessed-value districts. Although not related directly to property values, this difference may lead to inequities in current spending levels related to property wealth—the inequities found to be unconstitutional in the Serrano v. Priest decision. Therefore, we examine current revenues across school districts. Overall, school districts 43 that had a successful parcel tax in place raised $600 more per pupil than school districts that never proposed a parcel tax and $700 more than school districts that were unsuccessful (Table 3.14). These differences are only partly explained by parcel tax revenues, which averaged $375 per pupil for school districts with a successful election. There are also differences in other local taxes and some categorical programs.15 Thus, school districts that passed local parcel taxes were more successful at raising other local funds as well. Similar patterns exist for unified districts, where districts with parcel taxes in place raised $400 more per student. Table 3.14 Fiscal Characteristics of School Districts, by Parcel Tax Experience, 1986–2000 Did Not Proposed and Proposed Overall Propose Did Not Pass and Passed All School Districts Total current revenues per student Non–ad valorem taxes Parcel taxes 6,420 37 28 6,384 3 0 6,263 11 0 6,980 451 375 Unified School Districts Total current revenues per student Non–ad valorem taxes Parcel taxes 6,418 25 19 6,402 5 0 6,318 17 0 6,816 307 301 NOTE: Amounts are in constant year 2000 dollars. Summary In this chapter, we have examined how school districts use bond and tax measures and the effects of these measures on school district finances. We find that school districts relied more on bond measures than tax measures, possibly reflecting limitations on current expenditures because of school finance equalization rulings. About half of all districts ____________ 15The non–ad valorem category of revenues includes parcel taxes and other local revenue sources not subject to revenue limits. These taxes include sales taxes, maintenance assessment district funds, community redevelopment funds not subject to revenue limits, and penalties and interest from delinquent taxes not subject to revenue limits. 44 successfully passed a bond measure; of these districts, most passed only one measure. School districts in the Bay Area were the most successful historically in gaining voter approval for new bonds. School bond elections increased after the passage of Proposition 39 and passage rates dramatically increased throughout the state. The preliminary evidence suggests that the lower vote threshold increased the set of school districts proposing new measures—most notably expanding the ability of community college districts to raise funds locally. Of 67 new school bonds that were approved in March 2002, two-thirds (42) would not have passed at the old supermajority level. In examining school facility revenues, we find that school bond funds were an important component of capital expenditures—making up approximately 40 percent of capital revenue funds and about half of all local funds. The probability of proposing or passing a bond measure depends on enrollment size, enrollment growth, and average household income. The amount of money approved depends on enrollment, enrollment growth, and the assessed value of property in the school district. Districts that had higher assessed value raised more funds. This pattern in part reflects current debt limits, which are based directly on assessed value, and it has led to unequal capital spending across school districts with different levels of assessed value. School districts in the Bay Area were also more likely to propose and pass bond measures and also to have higher levels of capital spending. Finally, we find that parcel taxes were used by relatively few school districts but that school districts that were successful at passing a parcel tax generally re-approved the tax over time. Parcel taxes were most often proposed by Bay Area school districts and were used by smaller school districts that contain wealthier households. This may raise equity concerns because this pattern leads to different levels of current spending across districts with different property wealth. However, the amount of money raised per pupil was relatively small. School districts that proposed but were unsuccessful in passing a parcel tax had lower average spending than districts that did not propose a parcel tax; those that were successful in passing a tax spent $600 more per pupil per year. 45 4. City Fiscal Measure Elections and Their Effect on Revenues Cities are the level of government, after school districts, that propose the most fiscal measures. Cities had the smallest increase in state revenues following Proposition 13 and are most reliant on their own revenue sources. Cities also have access to a fairly wide array of local revenues including parcel taxes, sales taxes, and various business taxes.1 New revenue sources can also be used to fund a myriad of different services including police, fire, library services, trash collection, and general government services. As of 1997, there were 471 incorporated cities in California. From 1986 to 2000, 728 measures were placed on the ballot by 267 cities. The vast majority of measures were to raise taxes (586 out of 728). We will begin by briefly investigating bond elections, comparing the uses of these funds to those passed by school districts, and the demographic characteristics of cities that have and have not proposed bond measures. We will also examine how these measures have affected capital revenue sources. The main analysis of this chapter, however, will explore the characteristics of tax measures and how spending levels vary across cities that have or have not successfully passed new taxes using the ballot box. We will also discuss the prevalence of new tax and fee measures in the aftermath of Proposition 218, the 1996 statewide initiative that confirmed the requirement for voter approval for general taxes and expanded the requirements of voter approval to certain fees and assessments. Finally, we investigate the demographic characteristics that lead to use of the ballot box and compare how sources of revenues have ____________ 1This chapter expands on prior work done by researchers at PPIC on city governments and their reliance on different sources of revenue. Lewis and Barbour (1999) examined the role of the local sales tax on city government structure and Dardia (1998) explored the role of redevelopment zones in reallocating funds between county and city governments. 47 varied over time in cities that have and have not passed fiscal measures. Unfortunately, we are potentially missing some information on fiscal elections that occurred in off-cycle or odd-year elections in the early 1990s. We find that in the period for which we have complete ballot information, local measures were less likely to be proposed in off-cycle elections; in cities with on-cycle versus off-cycle mayoral elections, we find no difference in the probability of never having a tax measure or of never successfully passing one.2 Municipal Bond Elections Municipal bonds were usually used to fund capital projects or to purchase land or equipment—parkland purchases, fire and police construction projects or equipment purchases, and library construction. A cluster of seismic safety projects in the early 1990s followed the Loma Prieta earthquake, which we classified under general government or by the service provided by the building to be refurbished (Table 4.1). Passage rates varied substantially across types of bond measures—with much higher passage rates for hospital (80 percent) and flood control (75 Table 4.1 Number of Bond Measures Proposed and Passed, by Function, 1986–2000 Function General government Fire, police, jails Hospital and emergency services Recreation and parks Library Transportation Flood control Buildings Other No. of Measures Proposed 9 24 5 40 19 14 12 9 10 Passage Rate (%) 44 42 80 33 58 43 75 56 70 Total or average 142 49 ____________ 2We use the classification of cities into those that have on-cycle or off-cycle elections found in Hajnal, Lewis, and Louch (2002). 48 percent) measures than for other bond requests. Funding to buy parkland or to refurbish playgrounds was proposed most often and faced the lowest passage rate, passing only one-third of the time. This partly reflects a city re-proposing a bond measure after it failed on an earlier ballot, a pattern similar to what we found for school districts. The number of bond measures proposed by cities reached the highest point in 1990 with 22, following the Loma Prieta earthquake, then declined in the mid-1990s and increased again in 2000 (Figure 4.1). Passage rates have also gone up since 1986, although this increase in passage rates partly reflects the smaller number of measures placed on the ballot (Figure 4.2). This increase in approval rating beginning in 1998 is similar to results for school districts, where bond passage rates increased even before the passage of Proposition 39. Thus, it seems there was increased support on the part of voters for infrastructure projects even beyond school facilities. As Table 4.2 shows, bonds passed 45 percent of the time before 1996, 30 percent of the time in 1996–1997, and 76 percent of the time in the past few years. 40 35 30 25 20 15 10 5 0 1986 1987 1988 1989 1990 1991 1992 1994 1996 1997 1998 1999 2000 NOTE: 1993 and 1995 are omitted because of a lack of information about fiscal measures. Figure 4.1—Number of Bond Measures Proposed by Municipal Governments, 1986–2000 49 Number of measures Passage rate, % 100 90 80 70 60 50 40 30 20 10 0 1986 1987 1988 1989 1990 1991 1992 1994 1996 1997 1998 1999 2000 NOTE: 1993 and 1995 are omitted because of a lack of information about fiscal measures. Figure 4.2—Passage Rate of Bond Measures Proposed by Municipal Governments, 1986–2000 Table 4.2 Number of Bond Measures Proposed and Passed, by Timing, 1986–2000 Before 1996 In 1996–1997 After 1997 No. of Measures Proposed 111 10 21 Passage Rate (%) 45 30 76 No. of Measures per Year 14 5 7 Total or average 142 49 11 Regional Patterns in Bond Elections The Bay Area and the southern region have proposed more bond measures than other regions in the state (Table 4.3). This pattern is not surprising; of the 471 incorporated cities in the state in 1997, 100 (21 percent) are in the Bay Area and 192 (41 percent) are in the southern region. Passage rates vary, with the Bay Area having the highest rate at 62 percent, and the valley region having the lowest at 13 percent. In the northern region of the state, the 62 cities proposed only four bond 50 Table 4.3 Number of Bond Measures Proposed and Passed, by Region, 1986–2000 Region Northern Bay Area Valley Coastal Southern Total or average No. of Cities 62 100 75 42 192 471 No. of Measures Proposed 4 60 8 12 58 142 Passage Rate (%) 50 62 13 50 40 49 measures. These patterns are reminiscent of what we saw for school districts, with higher proposal and passage rates in the Bay Area. Distribution of Bond Measures Across Municipalities The vast majority of municipal bond measures were proposed and passed by very few cities. San Francisco proposed 27 measures of which 16 passed, and Los Angeles proposed 15 of which nine passed. Table 4.4 shows that 399 cities proposed no bond measures, 51 cities proposed a single measure, 12 cities proposed two measures, six cities proposed three measures, and Berkeley and San Diego proposed four measures. As noted above, Los Angeles and San Francisco proposed more than 10 measures each. Table 4.4 Distribution of Bond Measures Proposed by Cities, 1986–2000 No. of Measures Proposed 0 1 2 3 or 4 10+ Total or average No. of Cities 399 51 11 8 2 Passage Rate (%) 37 36 49 67 471 39 51 Only 25 cities, or 5 percent, had one successful bond measure, and only four cities (San Francisco, Los Angeles, Berkeley, and Oakland) passed three or more (Table 4.5). Berkeley and Oakland held four and three elections, respectively, and all seven bond measures passed. Table 4.5 Distribution of Bond Measures Passed by Cities, 1986–2000 No. of Measures Passed 0 1 2 3+ Total or average No. of Cities 438 25 4 4 Passage Rate (%) 85 92 83 471 39 Determinants of Municipal Government Bond Elections and Capital Revenues We next examine the characteristics of the cities that had successful bond elections (Table 4.6). Our sample is limited to 348 cities for which we have demographic information. The cities that passed bond measures are larger than cities that did not propose a bond election or were unsuccessful. They tend to have a lower percentage of homeowners in their cities, and they tend to be in counties with fewer special districts. As noted above, they also tend to be in the Bay Area. We have limited information on municipalities’ capital expenditures over time spent. As with school districts, we aggregate capital expenditures for municipalities for the period between 1992 and 2000. The 29 cities that proposed and passed a bond measure spent almost twice as much as those that proposed none ($2,390 and $1,260, respectively, on a per capita basis), which in turn spent slightly less than cities that proposed but were unsuccessful at passing a bond measure ($1,440). As we found for school districts, it seems that passing a bond measure is a major force behind the undertaking of capital spending projects. 52 Table 4.6 Demographic and Fiscal Characteristics of Cities, by Bond Measure Experience, 1986–2000 Characteristic Did Not Total Propose No. of cities 348 287 Capital Expenditures Per capita capital expenditures, 1992–2000, $ 1,347 1,260 Demographics Average population Density (population/sq. mi.) Real per capita income, $ % living in same house for 5 years % homeowner % over age 65 % nonwhite No. of special districts in county, 1997 62,460 4,451 22,689 45.5 57.4 11.6 27.1 55 41,419 4,466 21,969 45.8 57.6 11.5 27.4 58 Proposed and Did Not Pass 32 1,440 65,240 3,761 26,602 44.0 60.2 12.5 24.5 43 Proposed and Passed 29 2,390 267,631 5,056 25,495 44.2 53.0 12.5 27.0 43 NOTES: Capital expenditures data are from Cities Annual Report, published by the California State Controller’s Office. Expenditures in the 1992 to 2000 period are aggregated in real 2000 dollars. Demographic information is calculated from 1990 Census data. Municipal Tax Elections Over the last 15 years, California municipalities have proposed 586 tax measures. Taxes and fee elections were most often held to fund either general government services or new emergency 911 services (Table 4.7). Tax measures have similar passage rates across functions, with measures designed to fund general government passing slightly more often than other measures. Recall that general tax measures require a simple majority vote, whereas special taxes require a two-thirds majority vote. Thus, the similar passage rates result because although general taxes usually receive a smaller percentage of yes votes, they need a smaller majority to pass. Proposed tax measures for municipal finances have also taken many forms including parcel taxes, sales taxes, and specific taxes on utilities, hotel rooms, or new construction (Figure 4.3). Almost 40 percent of identified new taxes on local ballots were parcel taxes (200 of the 528 tax 53 Table 4.7 Number of Tax Measures Proposed and Passed, by Function, 1986–2000 Function General government Fire, police, jails Hospital and emergency services Recreation and parks Library Transportation Flood control Buildings Other No. of Measures Proposed 321 68 86 44 22 19 7 8 11 Passage Rate (%) 50 44 49 34 45 37 43 50 45 Total or average 586 47 250 200 Number of measures 150 100 50 0 Parcel Hotel Sales Consumer Business Missing Figure 4.3—Number of Fiscal Measures, by Type measures with identified type). Unlike property taxes, which are based on property value and are limited by law to 1 percent except to pay back bond measures, parcel taxes are not legislatively restricted. City parcel taxes are levied most often as a dollar amount per property (as in 146 of the 200 identified measures), occasionally listing different rates for 54 commercial or multiunit buildings (28 times). Fifty of the measures were for a limited amount of time—most frequently for seven years. Thus, city parcel taxes were typically passed as permanent measures in contrast to school district parcel taxes, which expired after a set amount of time. The average amount listed was $100, but a few cities proposed large taxes that were $500 or more. The median amount proposed was $50. Parcel taxes raise less money than property or sales taxes. An example of a typical parcel tax is one that was passed by multiple cities in Marin County for emergency services in 1994 and then renewed for another four years in 1998. These taxes were for paramedic services, and the $30 per parcel raised $150,895 in 1998 in Corte Madera (about $17 per capita). Similarly, an emergency service tax of $0.008 per square foot passed in Berkeley in 1998 and annually raises $2.1 million (about $20 per capita). Municipalities were next most likely to pass hotel taxes. Hotel taxes were proposed 127 times in 100 cities. These measures would often introduce a new tax or raise existing rates 2 or 3 percentage points. San Francisco and Los Angeles have the highest rates, at 14 percent. Burlingame raised $2.8 million per year when it increased its tax from 8 to 10 percent (about $100 per capita). The same percentage increase in San Mateo increased its 1998 revenues by $3.9 million ($42 per capita). Hotel tax revenues made up 8 percent of San Mateo’s 1998 general fund revenue. In 2000, Santa Rosa estimated that increasing its hotel tax by 3 percent from 9 to 12 percent would raise revenues by $900,000 ($6 per capita). Thus, the amount of money raised from hotel taxes varies depending on the rate and the number of rooms in a municipality and the vacancy rates. In the current economic downturn, municipalities are beginning to propose decreasing hotel taxes as a way to make their jurisdictions more attractive to travelers. Sales taxes were used by far fewer cities and were mainly proposed for general government services (eight times), public safety (five times), or transportation improvement (three times). Consumer taxes include mainly utility taxes, such as gas, electricity, and telephone services, and they usually fund general government activities. Business taxes usually take the form of business license taxes, although they also include taxes on admission fees to parks, libraries, or sporting events. Like consumer 55 taxes, they are mainly used to fund general government activities. Figure 4.3 lists numbers of measures by type. Passage rates also varied widely across types of taxes proposed, with hotel taxes and business taxes passing over half the time. Parcel taxes and consumer taxes and fees passed only 30 to 40 percent of the time (Figure 4.4). 100 90 80 70 Passage rate, % 60 50 40 30 20 10 0 Parcel Hotel Sales Consumer Business Figure 4.4—Passage Rate of Fiscal Measures, by Type Tax Measures Since Passage of Proposition 218 The number of tax measures proposed by city governments peaked in 1996—following the resolution of the uncertainty concerning the need for voter approval for general taxes and the passage of Proposition 218. Passage rates also increased in recent years. Recall that 1996 was the year that the court confirmed the legality of Proposition 62 and Proposition 218 was passed by state voters. Proposition 218 expanded voter requirements for user fees and confirmed voter approval requirements for general taxes. Indeed, many local governments had simultaneous elections with Proposition 218, gaining voter confirmation for taxes or fees that had been passed in prior years. We examine the number of elections that occurred before 1996, in 1996–1997, and after 1997 (Table 4.8). Most of the elections since 1998 (70 percent) were for general taxes rather than special taxes, reflecting the new requirements 56 Table 4.8 Number of Tax Measures Proposed and Passed, by Timing All taxes Before 1996 In 1996–1997 After 1997 No. of Measures Proposed 261 168 157 No. of Passage Measures Rate (%) per Year 41 33 55 84 50 52 Total or average 586 47 45 General government Before 1996 In 1996–1997 After 1997 130 50 16 82 50 41 109 51 36 Total or average 321 50 25 under Proposition 218. In subsequent years, the number of local elections stayed higher than it had been before 1996, reflecting the need for voter approval for more revenue sources. The second column in Table 4.8 shows that as use of the ballot box increased, so did passage rates, which peaked in the period surrounding Proposition 218. Also note that passage rates for general taxes remained constant with about half of these measures passing over our entire sample period. Regional Patterns in Municipal Tax Elections As with bond measures, we find that there were more tax elections in the Bay Area and the southern region than in the other regions of the state. There were also more elections in the Bay Area on a per city basis. The passage rates for tax measures varied dramatically across regions. Taxes were passed almost two-thirds of the time when they were proposed in the Bay Area, whereas in Southern California and coastal counties they passed less than 40 percent of the time (Table 4.9).3 ____________ 3Similar patterns exist across the different counties within the regions. Appendix Table D.1 includes county-level statistics on the number of cities in a county, the number of municipal elections held, and passage rates. 57 Table 4.9 Number of Tax Measures Proposed and Passed, by Region, 1986–2000 Region Northern Bay Area Valley Coastal Southern Total or average No. of Cities 62 100 75 42 192 471 No. of Measures Proposed 79 178 86 62 181 586 Passage Rate (%) 46 63 49 37 35 47 Distribution of Tax Measures Across Municipalities Almost half of all cities, 204 cities, had no local tax measures between 1986 and 2000, and another one-fourth had only one such measure (Table 4.10). Only 21 cities had five or more measures over this period. There is no clear relationship between passage rates and the number of times cities have gone to the ballot for financing. Table 4.10 shows that passage rates were highest for cities that used tax measures five or more times (55 percent) but were higher for cities that used them only once than for cities that used them four times (45 versus 39 percent). Of the 160 cities that successfully passed at least one new tax, 109 passed only one (Table 4.11). However, eight cities passed five or more new taxes; six of these in the Bay Area.4 Thus, municipalities used the ballot box in different ways. About half of all cities have not asked for voter approval, and of those that did place new taxes on their ballots, most passed only one. In contrast, a small group of cities repeatedly asked for, and received, voter approval to expand revenue sources. The use of the ballot box has expanded over time, with more cities asking for voter approval in the aftermath of Proposition 218. ____________ 4They are Berkeley, Larkspur, Oakland, Piedmont, Ross, and San Francisco. The other two cities that passed five or more taxes were Azusa in Los Angeles County and Isleton in the Central Valley. 58 Table 4.10 Distribution of Tax Measures Proposed by Municipal Governments, 1986–2000 No. of Measures Proposed 0 1 2 3 4 5+ Total or average No. of Cities 204 121 75 36 14 21 471 Passage Rate (%) 45 41 46 39 55 44 Table 4.11 Distribution of Tax Measures Passed by Municipal Governments, 1986–2000 No. of Measures Passed 0 1 2 3 4 5+ Total or average No. of Cities 311 109 29 9 5 8 471 Passage Rate (%) 0 71 77 89 85 84 44 Determinants of Municipal Tax Elections and Current Revenues What determines which cities went to the ballot box to raise new funds? We limit our analysis to the 348 cities that were incorporated before 1972 to better measure the changing reliance on different revenues over time and because we have accurate demographic information for them. Of the 348 cities, 145 cities did not propose any tax measures between 1986 and 2000, 86 cities proposed but did not pass any tax measures, and 117 cities proposed and passed at least one measure. 59 On average, cities that passed a tax measure were larger than those that did not go to the ballot box and those that were unsuccessful in receiving voter approval (Table 4.12). Cities with higher income or with fewer special districts were also more likely to successfully pass a new tax measure. This pattern could reflect differences in who provides specific services. If a city is responsible for more public services, the amount of money needed will be larger. Cities that passed new taxes had a lower percentage of nonwhite households than those that were not successful at raising new funds. Thus, income, population size, and the racial makeup of a city seem to affect whether cities successfully pass new taxes through the ballot box. Other demographic characteristics do not seem to differ across these three groups of cities. Which factors have made cities more likely to propose or pass a new tax using the ballot measure? It may be that certain cities were better able to respond to the pressures imposed by Proposition 13 and subsequent statewide restrictions on their funding sources before Proposition 13. Given the funding formulas used in allocating property tax revenues, we would expect certain characteristics to affect which cities would turn to the ballot box. The primary effect of Proposition 13 was to cut property tax levels, which would make cities that were more reliant Table 4.12 Demographic Characteristics of Cities, by Tax Measure Experience, 1986–2000 Characteristic No. of cities Did Not Total Propose 348 145 Proposed and Did Not Pass 86 Proposed and Passed 117 Average population Density (population/sq. mi.) Real per capita income, $ % living in same house for 5 years % homeowner % registered Democrat, 1999 % over age 65 % nonwhite No. of special districts in county, 1997 62,460 4,451 22,689 45.5 57.4 57.8 11.6 27.1 55.2 50,121 4,922 21,358 46.4 57.0 57.7 11.0 30.7 63.3 49,425 4,180 20,120 43.2 57.1 57.1 12.0 26.3 54.1 87,335 4,066 26,227 46.0 58.3 58.5 12.1 23.3 46.1 NOTE: Data are calculated from the 1990 Census unless otherwise noted. 60 on property tax revenues more likely to pass new taxes. In contrast, cities that had high levels of revenues from other sources before passage of Proposition 13 may be in better fiscal shape. We present information on average revenue levels and sources of revenues for the complete group of cities in our sample and we also split the sample into three subsamples based on tax measure experience. Cities that eventually passed a tax measure had similar levels of revenues before the passage of Proposition 13 to those that did not propose a tax measure, whereas the group of cities that proposed but did not pass a measure had lower levels of revenues even in the 1970s (Figure 4.5). These differences in per capita revenues increased following passage of Proposition 13. Cities that had been negatively affected went to the ballot box; those that were successful at passing a ballot measure maintained revenue levels on par with cities that did not propose new taxes; and those that were unsuccessful faced lower levels of revenues. Thus, cities that have not passed new taxes have historically spent less money than other cities, differences that expanded after Proposition 13. Did cities that went to the ballot box have a different tax structure in place before Proposition 13, and how did revenue structures change 1,200 1,000 Did not propose Proposed and did not pass Proposed and passed Revenue dollars (2000) 800 600 400 200 0 1972 1977 1982 1987 1992 1997 Figure 4.5—Average Per Capita General Revenue, by Measure Outcome, 1972–1997 61 following the limitations on property tax revenues? To answer these questions, we examine average revenue structures before and after Proposition 13 (Table 4.13). In 1972, before Proposition 13, cities that would eventually succeed at passing new tax measures had substantially more of their revenues coming from property taxes than cities that did not propose tax measures. From 1977 to 1982, property taxes per capita Table 4.13 Fiscal Characteristics of Cities, by Tax Measure Experience, 1986–2000 Number of cities General revenue Property tax Intergovernmental revenues Fees and assessments General revenue Property tax Intergovernmental revenues Fees and assessments General revenue Property tax Intergovernmental revenues Fees and assessments General revenue Property tax Intergovernmental revenues Fees and assessments General revenue Property tax Intergovernmental revenues Fees and assessments General revenue Property tax Intergovernmental revenues Fees and assessments Total ($) 348 1972 616 146 167 138 1977 792 173 254 155 1982 747 113 175 240 1987 864 129 173 299 1992 959 191 147 353 1997 982 164 154 365 Did Not Propose 145 635 131 174 147 813 168 255 165 769 116 169 250 886 126 178 306 1,007 191 149 385 1,010 161 154 384 NOTE: Amounts are in constant year 2000 dollars. Proposed and Did Not Pass 86 Proposed and Passed 117 568 627 129 177 155 167 128 134 732 810 136 205 242 261 145 151 683 766 86 130 176 184 218 245 777 902 101 154 169 171 269 310 848 981 152 220 137 153 313 342 852 1,043 137 188 138 168 320 374 62 declined dramatically for all cities, however, and as would be expected, cities that eventually passed a measure had a greater decline in these funds. As these cities successfully passed new measures including parcel taxes, their funds increased. The group of cities that were unsuccessful at passing new taxes consistently had the lowest amount of property tax revenues. Cities that did not propose ballot measures had a more diversified tax base to start with and became increasingly reliant on fees and assessments to raise funds. Note that over time, on average, all cities raised more of their money from fees and miscellaneous charges. This pattern occurred in other states as well but was more dramatic in California. Indeed, it was precisely this increased reliance on fees that led to placement of Proposition 218 on the ballot.5 In the prior section, we showed that cities that succeeded in passing a measure were larger and contained somewhat wealthier households than those that failed to pass new taxes or those that did not propose any new tax measures. They were also more reliant on property taxes historically and spent more money per capita than other cities. Cities that proposed but failed to pass new tax measures were somewhat poorer and had historically lower spending levels than the other two groups of cities. However, examining differences across average spending levels and characteristics does not clarify which factors are most important in driving cities to the ballot box. We therefore turn to a more nuanced examination of the relationship between city demographics and the amount of revenues raised by different cities (regression results are shown in Appendix Table D.2). To examine the estimated effects of these factors on the probability of proposing or passing at least one measure, we do a similar exercise to the one carried out for school districts. Cities that had higher levels of revenue in 1977 were less likely to propose new tax measures than those with lower levels of revenue, even controlling for the other characteristics of the city. We explore how changing city characteristics, such as household income or city population, affects the predicted probability of proposing or passing at least one tax measure for a given city, by examining the effect of changing a single characteristic (Table 4.14). For example, an ____________ 5See Doerr (2000). 63 Table 4.14 Estimated Change in Probability of Proposing and Passing Tax Measures Average city Per capita general revenue % of revenues from property tax Density % registered as Democrat % in the same house for 5 years No. of special districts Probability Probability of Probability of of Passing Proposing Passing If Proposed 63.7 35.6 57.6 Low High Low High Low High 66.0 60.9 36.9 34.0 56.6 58.9 61.2 66.8 30.3 42.9 50.9 65.9 66.7 58.0 39.5 28.8 60.7 51.8 57.1 70.3 29.8 42.1 53.4 62.0 68.3 57.9 36.7 34.4 55.0 60.8 68.7 51.0 40.5 25.1 60.4 51.0 NOTES: Low values correspond to the 25th percentile and high values to the 75th percentile of each variable. See Appendix Table D.3 for the median, 25th, and 75th percentile values of variables used in these simulation results. average city6 had a 64 percent chance of placing at least one measure on a ballot and a 36 percent chance of passing a tax measure over this period. If 1977 per capita revenue had been $900 instead of $700, the probability of placing a measure on the ballot would decrease to 61 percent, and the probability of passing to 34 percent.7 The reliance on the property tax plays a more dramatic role. If the average city had been highly reliant on property tax revenues and raised 26 percent of its funds in 1977 from the property tax, its probability of having an election would be 67 percent, and its chance of passing a new tax would be 43 percent. If the city had been less reliant on the property tax and property tax funds made up only 14.5 percent of its funds, its probability of proposing a new tax would be 61 percent and its probability of passage would drop to 30 percent. Thus, being more reliant on the property tax in 1977 increased the probability of passing a new tax measure by 40 percent. ____________ 6An average city is one with the median level of population, percentage homeowners, and other demographic characteristics listed in Table 4.13. 7In simulating the influence of a given variable, we will change the average characteristic to a low or high level; the low level corresponds to decreasing the variable in question from the average level to the value at the 25th percentile; increasing the characteristic entails a change to the 75th percentile. 64 The liberalness of voters in a city also plays a role in whether a new tax is proposed and passed. A city with an electorate of 67 percent registered Democrats on average proposes at least one ballot measure 70 percent of the time and passes at least one tax 42 percent of the time. In contrast, if the electorate was only 47 percent Democrat, a ballot measure is proposed 57 percent of the time and passed about one-third of the time. Do differences in city characteristics drive our regional differences? Is the higher use of ballot measures found in the San Francisco Bay Area related to the more liberal attitudes of voters and an earlier reliance on the property tax? To answer these questions, we examine differences in regional patterns once we control for other differences in city characteristics (Figure 4.6). A city in Northern California, the Bay Area, or the coastal region would be predicted to propose a tax measure 70 to 75 percent of the time, with cities in the northern region passing at least one ballot measure 40 percent of the time, and half the Bay Area cities passing at least one measure. Thus, part of the increased use of ballot measures in the Bay Area is related to other characteristics. Similarly, the decreased use of ballot measures in cities in the northern counties is related to the smaller population and density in these areas. In contrast, cities in the valley and Southern California are less likely to propose or pass a new tax when other differences are controlled for.8 Thus, we find that cities that were more reliant on property taxes before Proposition 13 are more likely to pass and propose new taxes, as are cities in the Bay Area and those with larger populations and more registered Democrats. Up until now, we have explored what makes a city more likely to go to the ballot box. We now turn to the effects of these decisions. First, we will examine whether the demand for revenues has changed systematically over time in ways related to passage of Proposition 13. Second, we explore whether the gaps in average revenues for cities that ____________ 8Appendix Table D.2 presents the regression coefficients from these models, with information on the effect of other demographic controls, and Table D.3 presents information on low, average, and high values of our different city characteristics. 65 Probability, % 100 90 80 70 60 50 40 30 20 10 0 Northern Bay Area Valley Proposing Passing Coastal Southern Figure 4.6—Estimated Probability of Proposing and Passing a Tax Measure, by Region did not propose, proposed but did not pass, and proposed and passed tax measures can be ascribed to differences in demographic characteristics of cities. We estimate demand for revenue models as we did for school districts presented in Chapter 3 (Appendix Table D.4). That is, we explore how per capita revenue levels are related to the size and density of cities and characteristics of their residents. We find similar patterns over time for most variables except for the role played by household mobility. Average revenue levels became more dependent on the percentage of a city’s population that had lived in the same house for more than five years after passage of Proposition 13. This result is not surprising, because before Proposition 13 was passed, assessed values were brought up to market rates on a periodic basis, whereas after Proposition 13 passed, assessed values were brought up to market rates only when property was sold. The effect of limited mobility on revenues increased beginning in 1987. We estimate that in 1997, in a city that had had a turnover rate of 40 percent in 1990, average revenues per capita would have been $796, whereas in a city with an average 66 turnover rate of 45 percent, average revenues per capita would have been $838.9 We next examine the role that proposing and passing at least one tax measure plays in the level of revenues after controlling for city demographic characteristics. We therefore examine how revenues would change for an average city10 if it had never proposed a tax election, had proposed and passed at least one tax measure, or had proposed but never passed a new tax measure. In 1997, a city with median demographic characteristics that had never proposed a tax measure had average per capita revenues of $874; a city that had proposed and passed a measure had virtually identical revenues per capita of $878; and a city that had proposed but never passed a ballot measure had revenues of only $774 (Figure 4.7). Controlling for demographics decreases the inequality 1,200 1,000 Did not propose Proposed and did not pass Proposed and passed Revenue dollars (2000) 800 600 400 200 0 1987 1992 1997 Figure 4.7—Estimated Real Per Capita General Revenue for a City with Average Demographics ____________ 9The importance of reassessing property is affected by how much appreciation occurs in house prices. Sheffrin and Sexton (1998) analyze the relationship between the market value and assessed value of property since the passage of Proposition 13 and how this relationship has affected property tax administration in California. They find that declines in property values helped to reduce the inequity in the property tax system during the early 1990s. 10That is a city with median characteristics. 67 between cities that have never proposed elections and those that proposed but did not pass a tax measure but does not completely explain these differences. Thus, it seems that the difference in city characteristics only partly explains differences in spending. Summary Since Proposition 13 was passed in 1978, very few city governments have proposed bond measures and most who did passed only one. The notable exceptions to this are San Francisco and Los Angeles. The predominant tax proposals are parcel taxes and hotel taxes to fund general government services. There has been an increased reliance on ballot measures in recent years following passage of Proposition 218. We also found that passage rates have increased. Municipal governments have become less reliant on the property tax, but overall per capita revenues have not declined. When we examined which cities went to the ballot box and which cities approved new tax measures, we found that cities that were historically more reliant on property taxes were more likely to ask for and receive authorization to implement new tax measures. We also found that proposal and passage rates were more likely in cities with a high percentage of registered Democrats. Denser cities and cities in the Bay Area were also more likely to ask for and receive voter approval for new tax measures. We also found that revenue levels have become increasingly dependent on household mobility, with cities that have a smaller population living in the same house for five years on average raising more money, because of higher levels of reassessment of property to market value. Finally, even after controlling for city characteristics, we found that revenue levels were lower for cities that had proposed but had failed to pass new tax measures, whereas cities that had successfully asked voters for new tax authority had similar spending levels to cities that did not propose new measures. 68 5. County and Special District Use of the Ballot Box In California, 4,628 non–school district jurisdictions can receive financing from local ballot measures. We have information on 1,461 elections that occurred in these jurisdictions in the period from 1986– 2000. Municipal governments proposed about half of these elections. County governments proposed 14 percent of these elections and special districts propose the remainder.1 In this chapter, we examine measures proposed by counties and special districts and explore how these governments used the ballot box to raise funds. Because of the differences in patterns found across regions in the state, we then look at the combined use of fiscal ballot measures across counties, cities, and special districts. The advantage in examining the use of ballot measures across all non–school districts is that we can make comparisons across services that are funded by different levels of governments. County Use of the Ballot Box County governments play a variety of roles, the two main ones being to act as an agent of the state, providing such specific services as social service programs and court services, and providing municipal services for unincorporated areas, or for counties with few municipalities, throughout the county. These include police, fire, trash collection, and many other services that resemble those provided by municipalities. To investigate how large a role a county plays in providing municipal services, we examine the percentage of local revenues controlled by the county (as compared to municipalities or special districts). In more rural ____________ 1For a discussion of the long-term trends in California’s local government structure and the possible effects of Proposition 13, see Lewis (1998). 69 counties concentrated in the northeastern region of the state, most nonschool district local expenditures are controlled by county governments, whereas more urbanized regions in the state rely more on municipal governments to provide services. Figure 5.1 maps the percentage of expenditures controlled by counties in 1997.2 In seven counties in the northern region and the Central Valley, over 80 percent of expenditures are controlled by the county governments. Recall that many of these counties were shown in Chapter 4 to have few municipal governments and also had very few ballot measures proposed by municipalities. 24–50 51–65 66–80 81–100 Figure 5.1—Percentage of 1997 Direct Expenditures Controlled by Counties ____________ 2Appendix Table E.1 includes county statistics for Figures 5.1, 5.4, 5.5, and 5.6. 70 County Bond Elections We consider a measure to be countywide if it was voted on by residents throughout the county. If a measure was applicable only to a small portion of the county, we classified the ballot measure as a special district election. There were relatively few countywide bond measures in our sample.3 We have information on 25 bond measures, all but three of which were proposed before 1996. Of the 25 measures proposed by county governments, eight of the nine measures under “fire, police, jails” were proposed to fund the construction or modernization of jail facilities (Table 5.1). County bond measures were proposed mainly in northern counties, the Bay Area, and southern counties (Table 5.2). Again, the increased ballot box use in northern counties partly reflects the lack of municipal governments in these counties. Table 5.1 Number of Bond Measures Proposed and Passed by Counties, by Function, 1986–2000 Function Fire, police, jails Hospital and emergency services Recreation and parks Library Other No. of Measures Passage Proposed Rate (%) 9 22 30 5 20 3 33 5 40 Total or average 25 24 County Tax Elections Countywide taxes were usually proposed by more rural counties to provide additional funds for general government services. About onethird of county taxes were for general government services and onequarter were proposals to fund emergency services, which include 911 ____________ 3Note that San Francisco bond measures were included under city measures rather than under county measures. 71 Table 5.2 Number of Bond Measures Proposed and Passed by Counties, by Region, 1986–2000 Region Northern Bay Area Valley Coastal Southern Total or average No. of Counties 22 8 15 6 6 57 No. of Measures Proposed 6 9 2 1 7 Passage Rate (%) 17 11 50 0 43 25 24 services and additional paramedic, police, or fire protection (Table 5.3). Passage rates also varied across functions, with the highest passage rates occurring for transportation measures. Similar to the results we found for cities, recreation and park taxes had the lowest passage rates of any specific function taxes. County governments also asked for a multitude of different tax types, including sales, hotel, and parcel taxes (Figure 5.2). The tax type Table 5.3 Number of Tax Measures Proposed and Passed by Counties, by Function, 1986–2000 Function General government Fire, police, jails Hospital and emergency services Transportation Recreation and parks Library Other Total or average No. of Measures Proposed 66 24 18 29 8 25 11 Passage Rate (%) 29 13 44 45 25 28 64 181 33 72 Number of measures 90 80 70 60 50 40 30 20 10 0 Parcel Hotel Sales Consumer Business Missing Figure 5.2—Countywide Measures, by Type of Tax most often requested at the county level was a sales tax increase and most initiatives proposed were to raise the sales tax by one-half cent (58 times), one-quarter cent (16 times), one cent (twice), or one-eighth cent (three times). Eighteen of these measures were for an explicit amount of time, usually 15–20 years. The lower passage rate found for counties is in part due to counties proposing sales taxes in multiple elections until one passes. Because a sales tax is broad-based, it raises considerably more revenue compared to a parcel tax or a transient occupancy tax. Passage rates are shown in Figure 5.3. Note that although most county tax measures had very low passage rates (33 percent), voters were very likely to pass such consumer taxes (77 percent) as utility fees and garbage collection charges. These passage rates are very different from the ones found for city tax measures—countywide hotel taxes and other business taxes had much lower passage rates than those for municipal taxes. Similar to what we found for cities, the number of measures proposed by counties peaked in the period surrounding Proposition 218. Before 1996, 13 measures a year were proposed, the number peaked at 18 per year during the 1996–1997 period, and fell to 15 in 1998–2000 73 Passage rate, % 90 80 70 60 50 40 30 20 10 0 Parcel Hotel Sales Consumer Business Figure 5.3—Passage Rate of Countywide Measures, by Type of Tax (Table 5.4). The increase in use corresponds to the period surrounding passage of Proposition 218, which required voter approval for general taxes and user fees. Table 5.4 Number of Tax Measures Proposed and Passed by Counties, by Timing Before 1996 In 1996–1997 After 1997 Total or average No. of Measures Proposed 100 35 46 181 Passage Rate (%) 32 43 26 No. of Measures per Year 13 18 15 33 14 Regional Patterns in County Tax Measures Almost one-third of county taxes were proposed in the northern region of the state, where 30 of the 58 measures proposed were to fund general government services (Table 5.5). Emergency and library service measures were proposed by counties in most regions. Library measures 74 Table 5.5 Number of Tax Measures Proposed by Counties, by Region and Function Function General government Fire, police, jails Hospital and emergency services Transportation Recreation and parks Library Other No. of Measures Proposed Northern Bay Area Valley Coastal Southern 66 30 14 14 4 4 24 5 961 3 18 4 29 6 83 25 6 11 4 554 0 774 5 121 1 566 2 330 1 Total 181 58 44 43 20 16 were the only type proposed more often at the county level than at the municipal level, with counties proposing 25 library tax measures and cities proposing 22. Overall, county measures passed about one-third of the time; however, there is wide variance in passage rates across regions and function (Table 5.6). Passage rates for county measures were lower in the northern counties (21 percent) and the Central Valley (26 percent). In contrast, counties in the Bay Area, coastal counties, and southern counties passed countywide measures twice as often, with Table 5.6 Passage Rate of Tax Measures, by Region and Function Function General government Fire, police, jails Hospital and emergency services Transportation Recreation and parks Library Other Average Passage Rate (%) Northern Bay Area Valley Coastal Southern 29 27 57 14 25 0 13 0 11 17 0 33 44 0 45 0 25 0 28 33 64 50 80 40 50 N/A 57 43 75 60 0 0 100 100 20 17 33 50 67 67 N/A 100 33 21 45 26 45 44 75 passage rates around 45 percent. Overall passage rates for transportation measures were higher than for other specified measures. The overall number of county measures by function by region is small, so the disparity in passage rates across some types of measures reflects the fact that most regions had only a few elections for each specified function. Special District Use of the Ballot Box Special districts also play an important role in providing local services. They include districts that are set up to provide a certain service, such as fire or water districts, or to provide general services to a specific area of a county (CFDs) or to aid development. CFDs are often formed as part of a development agreement. Often, for development to take place local officials require that new developments pay additional fees or taxes. These occur in Mello-Roos districts and are included as CFDs in our analysis. Counties in Southern California had many more special districts than those in the Bay Area or the northern region of the state (Figure 5.4). Numerous special districts also proposed tax and bond measures through the ballot box. We have information on 527 fiscal measures placed on the ballot between 1986 and 2000. Of these ballot measures, 461 were for taxes or fees and assessments and only 66 were for bond measures. Bond Elections Held by Special Districts CFDs, water districts, and park districts had the highest number of bond elections, each with around 15 measures (Table 5.7). Park district bond measures were typically to acquire property, and water district bond measures were to fund water main construction or treatment centers. CFD bond measures also fund water projects, transportation, or the purchase of open space and thus serve a similar function to other special districts. These different bond measures had vastly different passage rates, with water district measures passing 81 percent of the time, park district bonds passing only 15 percent of the time, and the CFD district bonds passing about half of the time. 76 1–15 16–30 31–50 51–75 76–111 Figure 5.4—Number of Special Districts, 1997 The number of bond measures proposed declined after 1996, similar to the pattern found for counties. However, passage rates increased after 1996—similar to the patterns we found for school districts and cities (Table 5.8). However, there were only eight special district bond elections proposed. Regional Patterns in Special District Bond Elections Unlike patterns found for other bond measures, special districts in coastal counties proposed bond measures most overall and per special district; these measures had a passage rate similar to that found in the Bay Area (Table 5.9). Passage rates across all regions except the southern counties were higher for special district bond elections than for bond elections proposed by cities or counties. 77 Table 5.7 Number of Bond Measures Proposed and Passed, by Type of Jurisdiction Jurisdiction Counties Cities Special districts CFD Fire, police, jails Recreation and parks Transportation Hospital Library Flood control Water district Other Total or average No. of Measures Proposed 25 142 66 17 2 13 1 10 1 2 16 4 Passage Rate (%) 24 49 50 47 100 15 0 40 100 100 81 0 233 46 Table 5.8 Number of Bond Measures Proposed and Passed by Special Districts, by Timing Before 1996 In 1996–1997 After 1997 No. of Measures Proposed 58 3 5 No. of Passage Measures Rate (%) per Year 47 7 67 2 60 2 Total or average 66 49 5 Tax Elections Held by Special Districts The vast majority of the tax measures proposed by special districts were parcel taxes. CFDs proposed 150 tax measures, for a variety of general and specific government services including road repair, fire protection, and public works (Table 5.10). These fiscal measures passed 41 percent of the time. Fire districts proposed 139 measures, and they 78 Table 5.9 Number of Bond Measures Proposed and Passed by Special Districts, by Region Region Northern Bay Area Valley Coastal Southern Total or average No. of Districts 707 228 772 180 330 2,217 No. of Measures Proposed 9 11 10 24 12 Passage Rate (%) 75 55 44 54 25 66 50 Table 5.10 Number of Tax Measures Proposed and Passed, by Type of Jurisdiction Jurisdiction Counties Cities Special districts CFD Fire, police, jails Recreation and parks Transportation Hospital Library Flood control Water district Other No. of Measures Proposed 181 586 461 150 144 46 26 32 14 13 13 23 Passage Rate (%) 33 47 46 41 51 35 50 50 50 46 77 39 Total 1,228 45 paid for fire protection services or emergency services including 911 programs. Fire districts had one of the highest passage rates, with proposals passing over half the time. Recreation and park districts proposed 46 measures to maintain existing park or recreation areas and, similar to patterns found for city and county measures to fund recreation 79 areas, these measures were most likely to fail, passing slightly more than one-third of the time. Even though water districts proposed only 13 measures, almost 80 percent of these measures passed. The other district category consists of special district types that proposed fewer than 15 measures and include utility districts among others. Examining ballot measures across special districts before and after the passage of Proposition 218, we find that proposals stayed constant on an annual basis with an average of about 35 tax measures being proposed per year throughout the period (Table 5.11). This is markedly different from what we found for cities and counties and reflects the fact that special districts consistently needed to gain voter approval throughout the 1986–2000 period. This is due to the classification of all special district taxes as special taxes and therefore subject to voter approval following Proposition 13 in 1978. Table 5.11 Number of Tax Measures Proposed and Passed by Special Districts, by Timing Before 1996 In 1996–1997 After 1997 Total or average No. of Measures Proposed 287 71 103 461 Passage Rate (%) 44 58 43 No. of Measures per Year 36 36 34 46 35 Regional Patterns in Special District Tax Elections Figure 5.5 maps the number of tax elections held by special districts between 1986 and 2000. Note that special districts in five counties, especially in the southern region and the Bay Area, proposed more than 20 measures over this period. In three counties, no special districts proposed measures, and 14 counties had a passage rate of less than 25 percent for these elections (Figure 5.6). The different patterns in proposal and passage rates across different areas of the state may be caused by differences in the types of districts. 80 0–5 6–10 11–20 21–40 41–51 Figure 5.5—Number of Tax Measures Proposed by Special Districts For all regions, the special districts proposing the most tax measures were emergency service and CFDs (Table 5.12). The Bay Area had the most transportation district elections, and there were more recreation and park measures placed on the ballot in the northern region of the state. Bay Area special districts had higher passage rates than other regions of the state across types of districts (Table 5.13). Northern counties had higher passage rates for emergency service districts than for measures proposed by other types of districts; these measures passed 50 percent of the time. Thus, part of what caused the lower passage rate overall in the northern counties was the larger percentage of measures to fund recreation and park services in these counties. 81 No special district measures 0–25 26–50 51–75 76–100 Figure 5.6—Passage Rate of Tax Measures Proposed by Special Districts, Total Table 5.12 Number of Tax Measures Proposed, by Region and Type of Special District Type of District CFD Fire, police, jails Hospital and emergency services Transportation Recreation and parks Library Water district Flood control Other Total No. of Measures Proposed Northern Bay Area Valley Coastal Southern 150 50 37 17 6 40 144 49 30 27 11 27 32 12 3 12 2 3 26 3 14 46 21 16 14 4 3 13 0 5 13 3 7 23 9 4 42 33 22 22 02 44 3 3 3 4 1 2 461 151 119 71 34 86 82 Table 5.13 Passage Rate of Tax Measures, by Region and Type of Special District Type of District CFD Fire, police, jails Hospital and emergency services Transportation Recreation and parks Library Water district Flood control Other Passage Rate 41 51 50 Northern Bay Area Valley Coastal Southern 46 51 41 17 30 51 60 37 73 48 50 100 50 0 33 50 0 64 25 0 100 35 19 63 33 33 0 50 25 67 50 50 67 77 N/A 100 100 0 75 46 33 43 N/A 50 100 35 30 25 0 50 100 Average 46 41 59 39 41 43 Ballot Use Across Different Types of Governments How does use vary across the state once differences in municipal structures are accounted for?4 Does the higher use of ballot measures by county governments in northern counties lead to aggregate use more like that found in other areas of the state? Our hypothesis is that, when looking at all non–school district governments as opposed to municipalities only, use of the ballot will expand in the northern region, where there are fewer city governments, and in the southern region, which is more dependent on special districts. We do find that use of the ballot box has increased in the northern counties. Surprisingly, there is a decline in the percentage of ballot measures proposed in Southern California as compared to when we restricted our analysis to municipal ballot measures. The percentage of measures in the Bay Area, more reliant on city governments, has also declined from 35 percent of ballot measures to 30 percent. The regional use of fiscal ballot measures can be found in Table 5.14. ____________ 4We exclude school districts from our aggregate analysis. This is due to the distinct uses for school district funds and the fact that no other level of government generally provides educational services. This information is also related to preliminary calculations done in McGuire and Rueben (1997). 83 Table 5.14 Number of Measures Proposed and Passed, by Region Region Northern Bay Area Valley Coastal Southern No. of Measures Proposed Total Bond Tax 311 20 291 419 82 337 219 18 201 152 36 116 360 77 283 Passage Rate (%) Total Bond Tax 40 45 39 58 56 59 39 28 40 42 50 40 38 38 38 Total or average 1,461 233 1,228 45 46 45 Marin County had the highest number of tax measures with 94 and a very high passage rate of 61 percent. Los Angeles County also had a high number of measures, 88, but a much lower passage rate of 40 percent. Alameda County had 71 tax measures and passed 72 percent. San Diego had 60 and passed 47 percent. Contra Costa and San Bernardino had 54 and 52 measures, respectively, but passed 37 and 33 percent. Twenty counties had fewer than 10 tax measures on the ballot (Figures 5.7 and 5.8).5 Thus, Bay Area counties and southern counties had more elections overall and overall passage rates were highest in the Bay Area. Do counties with more types of governments propose ballot measures more often and what leads to the differences in ballot use? Several factors tend to be associated with the variation in the use and passage of fiscal measures across counties. We ran regressions to examine the dependence of different counties on the ballot box. These regression results can be found in Appendix Table E.3. We controlled for similar factors to those considered in Chapter 4 when examining passage rates for cities. We find that the number of governments in a county increases the number of ballot measures proposed. We predict that for every additional government in a county, the number of tax proposals will increase by 18 percent. Whereas, on average, a county has 47 non– school district governments and proposes 21 tax measures, we estimate ____________ 5Appendix Table E.2 includes county-level statistics for Figures 5.7 and 5.8. 84 1–10 11–19 20–39 40–59 60–94 Figure 5.7—Number of Total Tax Measures Proposed, by County that if the number of governments increased by 20 the number of ballot measures would have increased by 3.6, in the 1986–2000 period. We also find that the predicted number of measures increases with population and with average county personal income. We find a smaller but still positive relationship between the predicted number of successful ballot measures and the number of governments in a county. We predict that an additional 20 governments will increase the number of successful tax measures by only one. Thus, although the average county passes nine measures, an increase of 20 local governments leads to successfully passing 10 measures. We also find that the percentage of registered Democrats in a county increases the number of passing measures. If we increase the percentage of registered Democratic voters by 10 percentage points, we predict an additional 3.4 successful tax measures. 85 0–25 26–50 51–75 76–100 Figure 5.8—Passage Rate of Tax Measures Proposed, by County Does proposing more ballot measures lead to more passed measures, or is it an indication that a government is putting the same measure on the ballot multiple times? On average, for every additional proposed measure, the number of successful measures increases by about one-half. Once we control for the number of measures proposed, the influence of the percentage of voters who are Democrats diminishes. This is partly due to the increased number of ballot measures proposed in counties that have a higher percentage of registered Democrats. Once we control for other county characteristics, we find that proposal and passage rates across regions are no longer statistically different from each other. Thus, the makeup of the local governance structure and the difference in liberalness found across different regions seem to drive the earlier patterns we found across regions. 86 Do passage rates differ by how new money will be spent? Also, do certain types of governments seem to be more successful at passing new ballot measures for certain functions than others? The overall findings are similar to those found by type of government (Table 5.15). General government and fire, police, and emergency services were proposed most often and generally had the highest passage rates. There are differences in passage rates for measures to fund similar functions based on the level of government proposing the tax. For example, fire and emergency services provided by special districts passed 53 percent of the time, taxes proposed by cities for similar functions passed 83 percent of the time, and taxes to fund fire services at the county level passed only 20 percent of the time. Voters were also more likely to approve a new bond measure for road construction or improvements than a tax measure. Transportation taxes are usually funded in one of three ways: a sales tax increase (42 measures, which passed 45 percent of the time), a parcel tax (18 measures, which passed 61 percent of the time), or an increase in a bridge fee or toll. New taxes or fees for transportation functions also vary by type of government passing the tax. County transportation measures passed 44 percent of the time, city measures passed 37 percent of the time, and special district measures to fund transportation or road improvements passed 62 percent Table 5.15 Number of Bond and Tax Measures Proposed and Passed, by Function Function General government Fire, police, jails Hospital and emergency services Recreation and parks Library Transportation Flood control Buildings Other No. of Measures Proposed Total Bond Tax 419 11 408 256 35 221 224 17 207 179 60 119 98 26 72 103 16 87 80 36 44 24 9 15 78 23 55 Passage Rate (%) Total Bond Tax 46 45 46 43 40 44 47 41 47 31 25 34 46 58 42 50 44 51 65 75 57 42 56 33 45 52 42 Total or average 1,461 233 1,228 45 46 45 87 of the time. Transportation measures were the only type to have higher passage rates at the county than the city level. We next look at whether use of the ballot box for fiscal measures increased in response to the passage of Proposition 218. As we found with cities, we find a marked increase in the use of the ballot box in more recent years for both bond and tax measures. Note that passage rates for tax measures have remained fairly constant—with a temporary increase following Proposition 218, whereas bond elections (like those for school districts) have had higher passage rates in more recent years (Table 5.16). Thus far, we have examined different aspects of ballot measures but have not yet examined which attributes of a ballot measure may lead to passage. To examine partial effects, we ran a simple logistic regression on the probability of a tax measure passing given the attributes outlined above. These attributes include the timing of the election,6 the level of government proposing,7 the function of the measure,8 the type of measure,9 and the region. The regression results can be found in Appendix Table E.4. Table 5.16 Number of Bond and Tax Measures Proposed and Passed, by Timing Before 1996 In 1996–1997 After 1997 No. of Measures Proposed Passage Rate (%) Total Bond Tax Total Bond Tax 840 192 648 41 43 41 289 15 274 53 40 54 332 26 306 46 77 44 Total or average 1,461 233 1,228 45 46 45 ____________ 6Whether the election is held before 1996, in 1996–1997, or after 1997, and whether it is a primary general election or an off-cycle election. 7Whether it is a county, city, or special district proposing the measure. 8Whether the tax will fund general government services, fire and police services, recreation and parks, transportation, or other specified uses. 9Whether the measure is a parcel tax, a sales tax, a business tax (including hotels), or a consumer tax. 88 After controlling for changes in what is placed on the ballot, passage rates have not increased or decreased significantly since 1996. Although more measures have been proposed, these new measures are not any more or less likely to pass. This result is due to the lower passage rate required (a simple majority) being offset by higher voter preference for funding some specific and more popular functions. We find a small effect on the passage of tax measures based on the point in the electoral cycle that a measure is proposed, with measures proposed in off-cycle periods passing 51 percent of the time, as compared to passage rates of around 40 percent for tax measures in general elections and primaries held during even years (Table 5.17). We also find differences in passage rates across types of governments, even when timing, type of tax Table 5.17 Estimated Change in Probability of Passing Tax Measures Average measure Probability of Passing 41 City measure County measure Special district measure 40 32 47 Primary Off-cycle General 43 51 40 Transportation measures Park measures 56 29 Business Consumer 56 36 Northern Bay Area Valley Coastal Southern 31 58 35 39 35 NOTE: Average measure is one with mean characteristics. 89 proposed, use of tax, and region are controlled for. Controlling for all other factors, county tax measures pass 32 percent of the time, city measures pass 40 percent of the time, and special district elections pass 47 percent of the time. This pattern may be due to the more specific aspect of special district elections. Certain uses of funds also have higher passage rates all else equal. Transportation measures pass 56 percent of the time, whereas park measures pass an estimated 29 percent of the time. Similarly, after controlling for other characteristics, we find that hotel taxes and other business taxes pass 56 percent of the time and consumer taxes pass 36 percent of the time. We do not find a statistically significant difference in passage rates between sales taxes and parcel taxes, despite differences in the raw passage rates. Finally, we find that once a tax measure is proposed in the Bay Area it will pass 58 percent of the time; an average passage rate in the rest of the state is 35 percent. Summary In this chapter, we broadened our analysis to examine the use of fiscal measures by county and special district governments. Counties and special districts, like cities, proposed tax measures far more often than bond measures. Counties proposed a variety of different tax measures, including more broad-based sales tax measures, whereas special taxes almost exclusively relied on parcel tax measures. Northern counties proposed a larger percentage of county measures, reflecting the lack of other governments in these counties. County measures also faced relatively low passage rates, reflecting the broader taxes proposed and a prevalence of fiscal measures intended to provide park or open space. Following the passage of Proposition 218, county governments were more likely to place a measure on the ballot. Special district measures were used throughout the state, but they did not increase in number following passage of Proposition 218. Special districts had higher overall passage rates than city and county government measures, despite requiring a supermajority for all ballot measures. Passage rates did vary substantially by type of government, with special districts that provide popular services, such as water districts, experiencing much higher passage rates than CFDs or park districts. 90 We examined the aggregate use of taxes by non–school district governments. We find that use rates and passage rates were still higher for Bay Area governments. In aggregate, ballot measure use was higher in counties with more local governments. Special districts had the highest passage rates for measures even when we controlled for the purpose of the tax and the type of tax being proposed. This pattern occurs despite the need for a supermajority for passage of these taxes. We also found little evidence of passage rates changing after passage of Proposition 218; although more ballot measures have been proposed, passage rates have stayed relatively constant. 91 6. Policy Considerations Statewide restrictions on local governments’ ability to raise funds have required that voters play a more active role in fiscal decisionmaking. As a result, understanding how new money is raised through the ballot box becomes increasingly important. California local officials are currently required to gain voter approval to pass new bond measures for capital expenditures (two-thirds majority), special taxes (two-thirds majority), general taxes (majority), and fees and assessments (majority of homeowners, supermajority of voters). As the economy weakens and existing instruments raise less money, local officials once again will face hard decisions about how to pay for needed government services. The detailed descriptions of successful and unsuccessful ballot measures may be instructive to elected leaders as they make these hard choices. This report has examined revenue patterns of local governments over the last 30 years. California’s local governance structure is more complicated than those found in many other states. In some counties, municipal governments provide the majority of local services; in others, special districts play an increasingly visible role. Overall, California local governments, especially school districts and counties, have become more reliant on state revenue sources. This trend differs from that found in the rest of the country, where local governments more often provide services with own-source revenues. As the state faces its own budget difficulties, however, it is cutting funds for local governments and instead authorizing more local governments to raise their own funds. In the closing days of the last legislative session, Governor Davis approved a bill allowing some cities to increase sales tax rates to pay for general services pending approval of city voters. Local officials therefore need to consider what revenues they need to fund which services and whether to ask voters for new general or specific taxes. Our analysis offers some lessons to policymakers as they decide what types of tax measures to propose to raise future funds. Our findings 93 suggest that if popular programs such as transportation measures or fire protection require funding, a dedicated tax, despite the required supermajority for approval, is more likely to garner voter support than a general tax. There are limitations concerning special taxes, as these funds are earmarked for specific spending areas and therefore will reduce local officials’ flexibility. However, if municipal governments need revenues to fund less popular programs such as library or park services, they might be more successful trying to pass a general tax. General taxes, however, face different approval rates depending on what kind of tax was proposed. Hotel taxes and business taxes were passed most often by cities. However, hotel tax increases have typically been proposed during periods of economic expansion and may discourage tourism during a recession. Proposing taxes at the county level is more problematic. Although passage rates depend on the purpose of the tax, generally county tax increases passed less often than city or special district measures. County taxes faced different approval rates with hotel taxes being passed less often than parcel taxes. The preliminary evidence indicates that in the aftermath of Proposition 39, more school districts successfully passed new bond measures and raised new funds. In light of predicted enrollment increases and current estimates that one-third of schools need major repairs, this is positive news. As more school districts are successful in passing debt, it may be necessary to examine the role that assessed value currently plays in capital financing, as school districts may start hitting their debt limit caps. Depending on the outcome of that examination, state officials may want to consider raising current debt limits.1 The state is also proposing new state bonds for school construction totaling $25 billion over the next few years. Historically, school districts applying for state money needed to raise matching funds, which meant that districts with less ability to raise money would be ineligible for state aid. Possible funding alternatives include allocating revenues to school districts on a per pupil basis or instituting a power equalization program ____________ 1Brunner and Rueben (2001) examine the distribution of facility funds across districts in the 1990s. The Legislative Analyst’s Office (2001) describes one alternative state funding system, whereby state capital funds would be distributed to districts on a per pupil basis annually. 94 whereby state funds are used to bring up the capital funds of districts with lower assessed value. Fiscal policy by plebiscite is part of California’s current system. Our results show that although statewide voters have increasingly expanded the number of fiscal measures that need approval, these measures need not curtail the functions of governments. Even as government officials have been required to expand voter input, passage rates for tax measures have increased. Indeed, Proposition 39 is evidence that voters are willing to ease fiscal restrictions and support public programs, possibly with a caveat of additional accountability, if funding is going to support programs they desire. Thus, as local ballot measures are used more frequently, both state and local officials will need to evaluate how their public finances are changing and what other changes are necessary in light of new statewide laws. The indications are that local ballot measures will play an increasingly visible role, and the conversation between voters and policymakers will continue. 95 Appendix A Information on Local Measures We gathered information on tax and bond measure questions for local governments in the state from four sources: State and Local Tax and Bond Ballot Measures: Summary of Election Results by the California Debt and Investment Advisory Committee (CDIAC);1 the California Ballot Monitor: A Guide to Local Land Use and Taxation Measures by the California Association of Realtors (REALTORS); the Coalition for Adequate School Housing (CASH), which had data on school district elections; and individual counties and the Internet. The CDIAC has comprehensive data for all tax and bond measures on the general election ballots for even years from 1986–2000 and for primary election ballots from 1990. However, CDIAC did not include elections that took place during odd years or on dates other than those of primary and general elections. The REALTORS dataset complements the CDIAC to a certain extent. It provides information on elections that occur in odd years and on elections that took place on non-primary and non–general election dates during the year. It has also complete coverage of Gann override measures. However, the REALTORS data cover only the 1987–1992 period. Data from these sources are complemented with the CASH data on school facilities elections. However, again, this dataset has the limitation that it provides information on school districts only. We also collected information on off-year elections since 1996 from county websites, newspaper articles after elections, and, as much as possible, from county election authorities. The propositions that appeared in different documents always listed the same outcome, which ____________ 1CDIAC was known as the California Debt Advisory Committee (CDAC) before 1996; the committee’s name and functions were expanded in response to the Orange County bankruptcy. 97 shows some consistency among the four sources. The number of voters and percentage of the electorate voting for the measure did differ slightly among the sources, but never by more than 5 percent. The breakdown of the observations is shown in Table A.1. The principal source of tax measure information is CDIAC, with more than 50 percent of the observations coming from it. For bonds, the source of the information is divided among CDIAC, REALTORS, and CASH, although the CASH dataset covers 80 percent of the bond elections. It may be easier and clearer to see where measures came from if we look at them yearly (Table A.2). 1993 and 1995 are the least complete years, with information coming only from CASH on school elections. Information on the remaining years came from a combination of sources up until 1992 (CDIAC, REALTORS, and CASH) and after 1992 (CASH and CDIAC) or the Internet and county offices, depending on whether it was an even or odd year. Information collected from the Internet came mainly from county election departments’ websites. Those without websites or not featured in any news coverage from other voting sources (mainly San Francisco Chronicle, Los Angeles Times, or Smartvoter.com websites among others) were contacted directly. Because we have the most complete information for school districts, it is useful to look at these sources excluding school district measures. Table A.3 shows the number of measures by year and source excluding school district elections. As mentioned above, the only information we have for 1993 and 1995 came from CASH data, which means that we Table A.1 Number of Measures, by Source and Type Source Tax Bond Total CDIAC 755 289 1,044 REALTORS 276 268 544 Both CDIAC and REALTORS 184 100 284 CASH 122 429 551 Counties and Internet 150 96 246 CASH and others (school districts) 137 520 657 Total 1,487 1,182 2,669 98 Table A.2 Number of Measures, by Source, Type, and Year Year 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 Total 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 Total CDIAC 52 65 50 31 98 175 162 122 755 16 1 24 45 36 85 82 289 CDIAC and REALTOR REALTORS Tax 40 50 58 61 16 66 79 30 60 276 184 Bond 45 36 26 59 27 45 73 28 27 2 268 100 Counties and Internet 5 109 1 31 4 150 63 33 96 CASH 11 10 2 1 3 1 2 29 12 14 2 16 10 9 0 122 8 24 12 8 9 8 9 45 22 85 27 50 50 62 10 429 lose these observations when we exclude school districts from the analysis. The major source for information on taxes was CDIAC. For bonds, the major source if we exclude school elections was REALTORS. 99 Table A.3 Number of Measures, by Source, Type, and Year, Excluding School District Elections Year 1986 1987 1988 1989 1990 1991 1992 1994 1996 1997 1998 1999 2000 CDIAC 50 63 48 28 93 163 159 117 CDIAC and REALTORS REALTORS Tax 34 44 55 41 14 59 45 18 56 Counties and Internet 6 103 1 26 5 Total 1986 1987 1988 1989 1990 1991 1992 1994 1996 1997 1998 1999 2000 721 15 1 10 11 11 10 13 196 170 Bond 19 18 15 27 13 26 18 7 11 141 5 3 Total 71 102 52 8 From all these sources, we constructed our final dataset, which includes information on the date of the election, measure letter (i.e., Proposition A), region, county, authorizing agency name and type, percentage of yes and no votes, whether the measure passed, the purpose 100 of the measure, the type of tax or amount of the bond, and the source of information. To check for completeness in the dataset, we looked at cities with off-cycle mayoral elections (that is, not on primary or general election dates). We checked whether cities in our dataset that had elections on off-cycle dates were less likely to have proposed a tax measure. If that were the case, we could have been missing information on those cities. Table A.4 indicates that this is not the case. Of the 348 cities in our sample for which we have election timing information, those with offcycle mayoral elections were only slightly more likely to be in the “did not propose” tax measure category. Even though 44 percent of cities with off-cycle elections did not propose any fiscal measure in our sample, and 40 percent of cities with on-cycle elections did not, the difference was not statistically significant. Finally, to further explore election data completeness, we looked at school district elections. We wanted to examine their distribution across years and election dates (primary, general, or other). Table A.5 gives this information. School district elections were more likely to be held on a date that does not correspond to a general or primary election. Districts proposed measures outside the general/primary cycle usually in March and April. School district elections were also more likely to occur during odd years, and presidential elections happened during even years. For information on the history of measures in our sample for specific localities or types of government, contact the authors. Table A.4 Number of Cities, by Election Cycle Timing No. of Cities On-cycle Off-cycle Missing Did Not Propose 72 51 22 Proposed and Did Not Pass 52 24 10 Proposed and Passed 59 40 18 Total 183 115 50 Total 145 86 117 348 101 Table A.5 School District Elections, by Type of Measure and Timing Election General Primary Other Tax Bond Total 90 343 433 65 245 310 104 361 465 Even years Odd years 110 464 574 149 485 634 Total 259 949 1,208 102 Appendix B Fiscal Information Fiscal information for local agencies was obtained from the U.S. Bureau of the Census, Census of Governments, Vol. 4, Government Finances, 1972, 1977, 1982, 1987, 1992, and 1997. These include fiscal data for all local governments in the United States including counties, municipalities and townships, school districts, and special districts surveyed by the Bureau of the Census for the U.S. Department of Commerce. Fiscal data for cities came from U.S. Bureau of the Census, Census of Governments, Vol. 4, Government Finances, data file on municipalities and townships. These include specific data for all municipalities and township governments in the United States. These datasets contain information on revenues, expenditures, population, and area for cities but lack demographic information. Demographic information came from the Decennial Population Census data, STF1a files (1980, 1990, and 2000) and the equivalent First Count STF, File B (1970). These are matched to 1972, 1982, and 1992 fiscal data, whereas for the odd years, information is averaged from the available years to 1975, 1985, and 1995 years (to be consistent with the two-year difference). The variables used are personal income (inflated to 2000 dollars), percentage of the population under age 18, over age 65, nonwhite, a homeowner, and has lived in the same house for five years. We have complete fiscal data for all years for 406 cities. If we add the demographic data, the number goes down to 348 cities with complete information for all years (see Table B.1). Here, we look at how these subsamples of cities differ. We divide our sample into all cities excluded for lack of demographic information and cities excluded because they were incorporated after 1972. We explore differences in fiscal policy and size of the cities, for which we look at the average per capita general revenues and population for the different subsamples. 103 Table B.1 Comparison of Cities in and out of Sample 1972 1977 1982 1987 1992 1997 Per Capita General Revenues $ (2000) All California No. of cities Complete information No. of cities Excluded Missing demographics No. of cities Incorporated after 1972 No. of cities 857 1,013 407 413 856 1,007 348 348 945 1,098 1,151 1,175 428 444 460 471 955 1,110 1,179 1,212 348 348 348 348 1,059 59 0 1,802 58 758 7 1,339 58 451 22 2,003 58 705 38 2,314 2,129 58 58 643 723 54 65 Average Size (Population) All California No. of cities Complete information No. of cities Excluded Missing demographics No. of cities Incorporated after 1972 No. of cities 36,905 38,717 42,066 46,933 51,329 54,368 406 413 428 444 460 471 42,893 45,270 50,048 56,736 62,460 66,442 348 348 348 348 348 348 1,589 1,934 2,303 2,788 3,424 4,039 59 58 58 58 58 58 17,720 20,640 24,544 31,048 33,375 0 7 22 38 54 65 Cities included in our sample have very similar per capita general revenues and are somewhat bigger than the overall average in the state. As we might expect, cities incorporated after 1972 and therefore not included in our sample are substantially smaller in terms of both population and average per capita revenues. Cities excluded for lack of demographic information seem to be relatively small cities with a high average per capita expenditure. However, our sample seems to be quite similar to California cities overall (Figure B.1). 104 Revenue dollars (2000) 1,500 1,400 1,300 1,200 1,100 1,000 900 800 700 600 500 1972 1977 1982 1987 Sample California 1992 1997 Figure B.1—Real Per Capita General Revenue for Cities, 1972–1997 105 Appendix C School District Information This appendix includes information on the number of bond measures (Table C.1) and parcel tax measures (Table C.5) proposed and passed by school districts in different counties. It then presents information on the regression estimates used to examine the effect of area demographics on school district bond elections. Table C.2 presents information on the proposal or passage of at least one bond measure. Table C.3 lists the points in the distribution of key variables used to carry out the simulations in Chapter 3. Finally, regressions of the determinants of capital spending are presented in Table C.4. 107 Table C.1 Number of School Districts and Number of Bond Measures Proposed and Passed, by County, 1986–2002 County Alameda Alpine Amador Butte Calaveras Colusa Contra Costa Del Norte El Dorado Fresno Glenn Humboldt Imperial Inyo Kern Kings Lake Lassen Los Angeles Madera Marin Mariposa Mendocino Merced Modoc Mono Monterey Napa Nevada Orange Placer Plumas Riverside Sacramento San Benito San Bernardino San Diego San Francisco San Joaquin San Luis Obispo No. of Districts 18 1 1 14 4 4 18 1 15 34 9 32 16 7 47 14 7 10 81 11 19 1 12 20 3 2 24 5 10 27 19 1 23 16 11 33 43 1 15 10 1986–2000 No. of Measures Passage Proposed Rate (%) 33 73 0 N/A 10 15 20 11 18 30 25 76 10 9 33 39 49 3 67 11 45 18 61 4 75 42 50 16 56 4 50 8 50 98 66 11 27 13 85 20 8 63 11 36 2 50 2 100 18 67 7 43 10 14 79 23 57 1 100 34 41 25 44 2 50 49 41 52 56 4 100 13 38 11 36 2001–2002 No. of Measures Passage Proposed Rate (%) 2 100 0 N/A 1 100 2 100 0 N/A 0 N/A 8 88 0 N/A 2 100 3 100 0 N/A 3 67 2 50 0 N/A 5 80 10 2 100 0 N/A 18 89 1 100 5 100 0 N/A 20 3 67 0 N/A 0 N/A 6 83 1 100 1 100 8 100 5 80 1 100 8 100 10 100 1 100 7 86 11 45 0 N/A 8 63 3 33 108 County San Mateo Santa Barbara Santa Clara Santa Cruz Shasta Sierra Siskiyou Solano Sonoma Stanislaus Sutter Tehama Trinity Tulare Tuolumne Ventura Yolo Yuba Table C.1 (continued) No. of Districts 23 23 33 11 25 1 29 6 40 27 12 18 11 47 12 20 5 5 1986–2000 No. of Measures Passage Proposed Rate (%) 26 81 24 58 48 75 5 60 17 24 0 N/A 5 20 14 43 27 85 29 48 8 25 4 25 0 N/A 20 40 4 50 33 52 13 46 0 N/A 2001–2002 No. of Measures Passage Proposed Rate (%) 6 100 1 100 10 90 3 100 2 100 0 N/A 10 3 100 7 86 8 100 0 N/A 1 100 0 N/A 6 100 2 50 2 100 10 10 109 Table C.2 Determinants of Bond Measure Proposals and Passage Rates, Regression Results Average daily attendance Proposed Any Passed Any Passed Any If Measures Measures Proposed All All All Districts Unified Districts Unified Districts Unified 0.042 0.017 0.027 0.018 0.000 0.011 (0.010) (0.011) (0.008) (0.009) (0.004) (0.012) % growth in average daily 0.224 0.593 0.225 0.450 0.255 0.473 attendance, 1989–1998 (0.107) (0.406) (0.104) (0.327) (0.231) (0.456) Assessed value per student –0.004 –0.047 –0.009 –0.028 –0.008 0.144 (0.005) (0.025) (0.008) (0.024) (0.014) (0.086) Mean household income 0.002 0.013 0.008 0.025 0.037 0.040 (0.003) (0.008) (0.003) (0.008) (0.011) (0.017) % over age 65 –0.942 –0.313 –0.554 0.010 2.496 –0.692 (0.967) (1.915) (0.982) (1.858) (1.959) (2.908) % nonwhite 0.614 0.114 0.416 –0.126 0.161 –0.130 (0.253) (0.457) (0.246) (0.422) (0.416) (0.587) % homeowner 0.439 0.393 –0.725 –2.079 –3.992 –5.314 (0.461) (1.043) (0.457) (0.999) (0.969) (1.837) Elementary school district –0.645 (0.125) –0.324 (0.120) 0.487 (0.180) High school district –0.054 (0.188) 0.132 (0.183) 0.293 (0.259) Northern –0.069 –0.527 –0.262 –0.334 –0.309 –0.056 (0.193) (0.345) (0.192) (0.337) (0.279) (0.434) Bay Area 0.524 0.303 0.615 0.532 0.703 0.248 (0.167) (0.306) (0.159) (0.281) (0.318) (0.451) Valley –0.108 0.105 –0.233 –0.069 –0.127 –0.272 (0.150) (0.286) (0.142) (0.249) (0.213) (0.306) Coastal 0.028 –0.559 0.058 –0.237 0.017 –0.110 (0.244) (0.390) (0.233) (0.365) (0.371) (0.507) Constant –0.393 –0.676 –0.237 –0.079 1.067 1.521 (0.423) (0.939) (0.415) (0.873) (0.885) (1.451) No. of observations 726 246 726 246 431 192 NOTES: Robust standard errors are in parentheses. 110 Table C.3 Distribution of Key Regression Variables Average daily attendance Average daily attendance growth, 1989–1998 Assessed value per student, $ Mean household income, $ % homeowners Median 2,211 119 397,874 40,754 64.7 25th 75th Percentile Percentile 461 7,039 107 255,077 32,712 56.4 132 669,118 51,232 73.1 111 Table C.4 Determinants of Per Pupil Capital Revenue, 1992–2000 Ln average daily attendance Total Capital Revenue per Student All All Districts Unified Districts Unified 0.312 0.132 0.204 0.084 (0.041) (0.059) (0.043) (0.060) Ln growth in average daily attendance 0.429 1.210 0.393 1.158 (0.113) (0.223) (0.110) (0.219) Ln assessed value per student 0.424 0.319 0.355 0.280 (0.092) (0.146) (0.089) (0.144) Ln mean household income –0.217 0.214 –0.218 0.104 (0.219) (0.305) (0.213) (0.301) % over age 65 –1.331 2.098 –1.081 2.329 (1.019) (1.493) (0.989) (1.465) % nonwhite 0.148 0.388 –0.004 0.359 (0.265) (0.329) (0.258) (0.323) % homeowner 0.842 0.046 0.763 0.140 (0.475) (0.735) (0.465) (0.731) Elementary school district 0.094 (0.128) 0.148 (0.125) High school district –0.345 (0.199) –0.297 (0.194) Northern 0.071 –0.088 0.014 –0.046 (0.204) (0.263) (0.199) (0.258) Bay Area 0.721 0.519 0.557 0.466 (0.158) (0.194) (0.155) (0.191) Valley 0.029 0.273 –0.003 0.259 (0.153) (0.193) (0.149) (0.189) Coastal 0.272 0.385 0.210 0.448 (0.245) (0.290) (0.238) (0.285) Proposed any bond measure 0.432 0.346 (0.171) (0.186) Passed any bond measure 0.412 0.247 (0.179) (0.215) Constant 1.056 –1.609 2.451 0.055 (2.234) (2.847) (2.178) (2.842) No. of observations 726 246 726 246 R-squared 0.2 0.25 0.25 0.28 NOTES: Robust standard errors are in parentheses. 112 Table C.5 Number of Parcel Tax Measures Proposed and Passed by School Districts, by County, 1986–2000 County Alameda Alpine Amador Butte Calaveras Colusa Contra Costa Del Norte El Dorado Fresno Glenn Humboldt Imperial Inyo Kern Kings Lake Lassen Los Angeles Madera Marin Mariposa Mendocino Merced Modoc Mono Monterey Napa Nevada Orange Placer Plumas Riverside Sacramento San Benito San Bernardino San Diego San Francisco San Joaquin San Luis Obispo San Mateo Santa Barbara No. of Measures Passage Rate Proposed (%) 16 81 0 N/A 0 N/A 0 N/A 10 0 N/A 20 50 0 N/A 0 N/A 0 N/A 10 10 0 N/A 0 N/A 3 67 0 N/A 0 N/A 0 N/A 24 29 0 N/A 48 85 10 2 50 0 N/A 0 N/A 0 N/A 50 0 N/A 10 30 4 75 0 N/A 0 N/A 10 0 N/A 1 100 30 0 N/A 10 0 N/A 16 69 0 N/A 113 Table C.5 (continued) County Santa Clara Santa Cruz Shasta Sierra Siskiyou Solano Sonoma Stanislaus Sutter Tehama Trinity Tulare Tuolumne Ventura Yolo Yuba No. of Measures Passage Rate Proposed (%) 24 50 6 17 0 N/A 0 N/A 0 N/A 3 33 24 58 0 N/A 0 N/A 0 N/A 0 N/A 6 17 0 N/A 20 4 100 0 N/A 114 Appendix D Municipal Election Information Table D.1 presents information on the distribution of cities and municipal tax elections across counties. It also contains information on the probability of proposing tax measures as well as city revenue demand regressions. Table D.2 estimates a probit model on the probability of proposing or passing at least one tax measure. The revenue and demographic data came from Census of Governments (per capita general revenues and percentage of general revenues coming from property tax) and the Decennial Census (per capita income, population, density, percentage of registered Democrats, percentage homeowners, and percentage living in the same house for five years). Information on the number of special districts in a county came from the California Controllers’ office. Information on the points in the distribution of variables used in the simulations in Chapter 4 are presented in Table D.3. Table D.4 uses a natural log regression model, correcting for within-county heteroskedasticity. All demographic controls came from the Decennial Census. The 1982 and 1992 regressions use 1980 and 1990 Census data, whereas even years have been averaged from Census ones. 115 Table D.1 Number of Tax Measures Proposed and Passed by Cities, 1986–2000 County Alameda Alpine Amador Butte Calaveras Colusa Contra Costa Del Norte El Dorado Fresno Glenn Humboldt Imperial Inyo Kern Kings Lake Lassen Los Angeles Madera Marin Mariposa Mendocino Merced Modoc Mono Monterey Napa Nevada Orange Placer Plumas Riverside Sacramento San Benito San Bernardino San Diego San Francisco San Joaquin San Luis Obispo San Mateo No. of Cities 14 0 5 5 1 2 19 1 2 15 2 7 7 1 11 4 2 1 88 2 11 0 4 6 1 1 12 5 3 33 6 1 24 5 2 24 18 1 7 7 20 No. of Measures Proposed 52 0 1 7 2 1 22 0 3 22 4 7 6 0 13 1 3 0 77 3 39 0 4 2 0 1 21 2 5 19 15 0 36 14 5 26 17 11 1 13 23 Passage Rate (%) 75.0 N/A 100.0 28.6 0.0 100.0 40.9 N/A 66.7 45.5 25.0 14.3 33.3 N/A 15.4 0.0 33.3 N/A 36.4 0.0 69.2 200.0 50.0 100.0 N/A 100.0 52.4 50.0 60.0 31.6 26.7 N/A 30.6 78.6 20.0 23.1 64.7 90.9 0.0 30.8 73.9 116 County Santa Barbara Santa Clara Santa Cruz Shasta Sierra Siskiyou Solano Sonoma Stanislaus Sutter Tehama Trinity Tulare Tuolumne Ventura Yolo Yuba Table D.1 (continued) No. of Cities 7 15 4 3 1 9 7 9 9 2 3 0 8 1 10 4 2 No. of Measures Proposed 7 20 4 2 3 4 9 14 15 3 1 0 0 3 12 8 3 Passage Rate (%) 28.6 50.0 25.0 50.0 0.0 75.0 44.4 50.0 60.0 33.3 0.0 N/A N/A 0.0 33.3 87.5 33.3 117 Table D.2 Determinants of Tax Measure Proposals and Passage Rates, Regression Results 118 City per capita general expenditures, 1977, $1000s (2000) % of city revenues from property tax, 1977 Real per capita income,1990, $1000s (2000) City population, 1990 (millions) Density, 1990 (population per sq. mi.) % registered as Democrat, 1999 % homeowners, 1990 % in same house for 5 years Charter city No. of special districts, 1997 Proposed Any Tax Measures –0.374 (0.179) 1.285 (0.802) 0.330 (0.218) 0.784 (0.705) –0.068 (0.029) 0.018 (0.007) –0.001 (0.009) –0.025 (0.011) –0.159 (0.180) –0.007 (0.003) Proposed Any Tax Measures –0.359 (0.185) 1.528 (0.828) 0.133 (0.280) 1.060 (0.790) –0.053 (0.032) 0.009 (0.009) 0.000 (0.009) –0.026 (0.011) –0.176 (0.185) –0.001 (0.003) Passed Any Tax Measures –0.216 (0.186) 2.882 (0.846) 0.427 (0.227) 1.207 (0.783) –0.087 (0.034) 0.017 (0.007) –0.010 (0.009) –0.006 (0.011) –0.267 (0.194) –0.007 (0.003) Passed Any Tax Measures –0.185 (0.192) 3.199 (0.871) 0.232 (0.285) 1.291 (0.814) –0.063 (0.036) 0.007 (0.009) –0.012 (0.010) –0.006 (0.011) –0.285 (0.196) –0.003 (0.004) Passed Tax If Proposed 0.158 (0.338) 3.304 (1.169) 0.445 (0.317) 1.435 (1.376) –0.067 (0.045) 0.011 (0.010) –0.015 (0.012) 0.013 (0.014) –0.346 (0.262) –0.004 (0.004) Passed Tax If Proposed 0.120 (0.336) 3.437 (1.188) 0.378 (0.398) 1.328 (1.458) –0.047 (0.047) 0.005 (0.013) –0.019 (0.013) 0.014 (0.014) –0.376 (0.271) –0.005 (0.005) Table D.2 (continued) 119 Northern Proposed Any Tax Measures Bay Area Valley Coastal Constant No. of observations NOTES: Robust standard errors are in parentheses. 0.158 (0.880) 348 Proposed Any Tax Measures 0.595 (0.307) 0.654 (0.287) –0.062 (0.236) 0.741 (0.295) 0.416 (1.177) 348 Passed Any Tax Measures –1.540 (0.908) 348 Passed Any Tax Measures 0.477 (0.312) 0.671 (0.294) 0.314 (0.254) 0.157 (0.302) –0.971 (1.219) 348 Passed Tax If Proposed –1.883 (1.283) 203 Passed Tax If Proposed 0.214 (0.380) 0.336 (0.412) 0.516 (0.332) –0.355 (0.375) –1.300 (1.760) 203 Table D.3 Distribution of Key Regression Variables Per capita general revenue, $ % of revenues from property tax Density (population per sq. mi.) % Democrat % in the same house for 5 years No. of special districts Median 698 19.6 3,514 57.1 45.0 48 25th Percentile 535 14.5 2,343 47.3 40.0 29 75th Percentile 899 26.2 5,704 67.4 51.1 93 Table D.4 Demand for City Revenues, Controlling for Which Cities Proposed and Passed Tax Measures Ln population Per Capita General Revenues 1977 1982 1987 1992 1997 0.032 0.053 0.070 0.056 0.022 (0.023) (0.019) (0.018) (0.023) (0.023) Ln real per capita income –0.162 –0.161 0.053 0.112 0.140 (0.145) (0.126) (0.123) (0.134) (0.109) Ln density –0.179 –0.186 –0.189 –0.189 –0.157 (0.066) (0.050) (0.059) (0.078) (0.075) % under age 18 –0.034 –0.044 –0.035 –0.029 –0.035 (0.007) (0.006) (0.006) (0.009) (0.008) % over age 65 –0.005 0.000 0.003 0.003 0.000 (0.007) (0.007) (0.006) (0.005) (0.007) % nonwhite 0.011 0.010 0.007 0.005 0.006 (0.003) (0.002) (0.003) (0.003) (0.003) % in same house for 5 years –0.003 –0.001 –0.008 –0.009 –0.011 (0.003) (0.002) (0.003) (0.003) (0.004) Proposed a tax measure, 1986–2000 –0.116 –0.152 –0.156 –0.165 –0.145 (0.044) (0.033) (0.040) (0.048) (0.047) Passed a tax measure, 1986–2000 0.113 0.095 0.103 0.100 0.126 (0.049) (0.046) (0.054) (0.052) (0.056) Constant 10.416 10.116 8.132 7.689 7.679 (1.552) (1.266) (1.352) (1.530) (1.231) No. of observations 348 348 348 348 348 R-squared 0.21 0.27 0.27 0.24 0.24 NOTE: Robust standard errors are in parentheses. 120 Appendix E County and Special District Election Information This appendix contains information on county and special district elections. Tables E.1 and E.2 present information underlying the maps in Chapter 5. Table E.3 estimates a linear model, at the county level, of the number of ballot measures proposed and passed. Demographic controls came from the Decennial Census. Table E.4 estimates a probit regression on the probability of an election measure passing once proposed using election characteristics as independent variables. 121 Table E.1 Percentage of Direct Expenditures Controlled by Counties, Number of Special Districts, and Number of Tax Measures Proposed and Passed by Special Districts, 1986–2000 County Alameda Alpine Amador Butte Calaveras Colusa Contra Costa Del Norte El Dorado Fresno Glenn Humboldt Imperial Inyo Kern Kings Lake Lassen Los Angeles Madera Marin Mariposa Mendocino Merced Modoc Mono Monterey Napa Nevada Orange Placer Plumas Riverside Sacramento San Benito San Bernardino San Diego San Francisco San Joaquin % of Direct Expenditures Controlled by Counties 42.1 84.7 69.8 60.7 88.3 64.0 51.4 68.6 56.9 54.8 65.8 64.6 46.8 56.9 66.0 57.8 66.2 84.6 53.5 64.3 51.2 77.3 59.0 68.2 83.0 55.0 50.6 63.8 52.0 46.7 52.8 53.8 55.8 70.8 23.7 57.2 42.8 N/A 59.8 Special Districts No. of No. of Measures Passage Districts Proposed Rate (%) 14 9 56 3 10 17 1 0 40 5 0 40 4 50 40 1 0 45 23 39 20 2 100 49 24 42 100 5 40 37 0 N/A 48 5 40 21 2 50 23 7 29 100 15 20 35 1 0 37 5 40 25 12 33 93 9 56 9 20 28 51 57 4 1 100 41 10 50 63 0 N/A 29 9 67 21 3 100 48 12 58 5 3 33 25 15 60 29 7 43 51 19 37 36 10 50 66 8 38 66 8 75 9 2 50 56 22 45 65 38 39 0 00 102 8 13 122 County San Luis Obispo San Mateo Santa Barbara Santa Clara Santa Cruz Shasta Sierra Siskiyou Solano Sonoma Stanislaus Sutter Tehama Trinity Tulare Tuolumne Ventura Yolo Yuba Table E.1 (continued) % of Direct Expenditures Controlled by Counties 62.1 45.0 60.2 52.5 56.0 55.2 60.2 74.1 42.4 53.0 61.1 56.8 81.6 92.7 47.0 90.3 57.5 49.4 75.8 Special Districts No. of No. of Measures Passage Districts Proposed Rate (%) 32 2 0 28 8 88 36 9 22 21 9 89 26 6 67 35 1 100 14 0 N/A 43 11 45 43 1 100 44 14 64 56 2 0 27 13 15 33 1 0 16 5 60 111 5 40 13 10 60 29 3 0 29 0 N/A 41 2 0 123 Table E.2 Number of Tax Measures Proposed and Passed by Non–School District Local Governments, by County, 1986–2000 County Alameda Alpine Amador Butte Calaveras Colusa Contra Costa Del Norte El Dorado Fresno Glenn Humboldt Imperial Inyo Kern Kings Lake Lassen Los Angeles Madera Marin Mariposa Mendocino Merced Modoc Mono Monterey Napa Nevada Orange Placer Plumas Riverside Sacramento San Benito San Bernardino San Diego San Francisco San Joaquin San Luis Obispo San Mateo Santa Barbara No. of Measures Passage Proposed Rate (%) 71 72 10 3 33 17 24 11 18 4 25 54 37 9 33 29 41 30 47 8 13 14 21 11 45 8 38 33 18 20 8 38 13 38 88 40 7 14 94 61 3 67 18 39 4 75 9 67 4 100 37 49 8 63 24 50 30 33 36 31 15 40 45 31 30 57 14 29 52 33 60 47 11 91 11 18 17 24 33 79 17 29 124 Table E.2 (continued) County Santa Clara Santa Cruz Shasta Sierra Siskiyou Solano Sonoma Stanislaus Sutter Tehama Trinity Tulare Tuolumne Ventura Yolo Yuba No. of Measures Passage Proposed Rate (%) 35 66 14 50 5 40 5 40 16 56 14 57 33 48 18 50 19 21 5 40 8 38 5 40 20 45 18 28 9 78 11 9 125 Table E.3 Determinants of Number of Measures Proposed and Passed by Counties, 1986–2000 No. of governments Median Value 40 No. of Measures Proposed 0.178 (0.074) No. of No. of Measures Measures Passed Passed 0.056 –0.042 (0.046) (0.021) Per capita general expenditures, 1997, $1000s (2000) 2 –3.828 –2.464 –0.341 (5.172) (3.178) (1.389) County per capita property tax, 1997, $1000s (2000) 0.417 4.766 2.863 0.219 (15.755) (9.680) (4.212) Real per capita income, 1990, $1000s (2000) 23 1.732 0.972 0.012 (0.343) (0.210) (0.114) County population, 1990 (thousands) 134 0.005 0.002 –0.001 (0.002) (0.001) (0.001) Change in population, 1980 to 1990 27 –0.068 –0.122 –0.085 (0.203) (0.125) (0.054) % homeowners, 1990 62 0.672 0.477 0.104 (0.505) (0.310) (0.137) % living in same house for 5 years, 1990 41 –0.734 –0.427 –0.020 (0.624) (0.383) (0.169) % registered as Democrat, 1990 44 0.239 0.340 0.207 (0.259) (0.159) (0.070) % of population nonwhite 80 –0.166 –0.214 –0.122 (0.268) (0.165) (0.072) Proposed a tax measure in period, 1986–2000 0.555 (0.039) Constant –34.525 –21.391 –2.241 (33.547) (20.611) (9.061) No. of observations 58 58 58 R-squared 0.71 0.66 0.93 NOTE: Robust standard errors are in parentheses. 126 Table E.4 Determinants of the Probability of a Tax Measure Passing Year 1996–1997 Probability of Passing 0.111 (0.112) After 1997 –0.005 (0.095) Primary election 0.073 (0.092) Off-cycle election 0.268 (0.165) Proposed by county –0.227 (0.133) Proposed by special district 0.178 (0.111) Fire protection measure 0.092 (0.176) Emergency services measure –0.169 (0.134) Hospital measure 0.101 (0.246) Parks and recreation measure –0.381 (0.169) Transportation measure 0.339 (0.184) Other function measure (non–general government) 0.005 (0.147) Business tax 0.418 (0.139) Consumer tax –0.083 (0.161) Sales tax –0.162 (0.163) Northern –0.100 (0.119) Bay Area 0.578 (0.109) Valley 0.010 (0.129) 127 Table E.4 (continued) Coastal Probability of Passing 0.105 (0.147) Constant –0.483 (0.150) No. of observations 1,141 NOTE: Robust standard errors are in parentheses. 128 Bibliography Balsdon, Ed, Eric Brunner, and Kim Rueben, “Private Demands for Public Capital: Evidence from California School Bond Measures,” San Diego State University Working Paper, San Diego State University, San Diego, California, 2002. Bergstrom, Theodore C., Daniel L. Rubinfeld, and Perry Shapiro, “Micro-Based Estimates of Demand Functions for Local School Expenditures,” Econometrica, Vol. 50, No. 4, 1982, pp. 1183–1205. Borcherding, Thomas E., and Robert T. Deacon, “The Demand for the Services of Non-Federal Governments,” American Economic Review, Vol. 62, No. 5, 1972, pp. 891–901. Brokaw, Alan J., James R. Gale, and Thomas E. Merz, “The Effect of Tax Price on Voter Choice in Local School Measures: Some New Evidence from Michigan,” National Tax Journal, Vol. 51, No. 1, 2001, pp. 527–540. Brunner, Eric, and Kim S. Rueben, “Financing New School Construction and Modernization: Evidence from California,” National Tax Journal, Vol. 54, No. 3, 2001, pp. 53–60. Cain, Bruce E., Ellyce Cooper, Sara Ferejohn, and Carrie Potter “California Library Measures: The Determinants of Success and Failure,” working paper 96-7, Institute of Government Studies, University of California, Berkeley, California, 1996. California Association of Realtors, California Ballot Monitor: A Guide to Local Land Use and Taxation Measures, Sacramento, California, December 1992. California Debt Advisory Committee, State and Local Tax and Bond Ballot Measures: Summary of Election Results, Sacramento, California, various issues, 1986–2002. 129 California Debt and Investment Advisory Committee, “Local Tax Measures Dominate November Election,” Debt Line, Vol. 16, No. 1, Sacramento, California, 1997. California Senate Committee on Local Governments, An Inventory of Local Tax Powers, Sacramento, California, 1996. Coalition for Adequate School Housing, School District Elections (data file), Sacramento, California, 2002. Dardia, Michael, Subsidizing Redevelopment in California, Public Policy Institute of California, San Francisco, California, 1998. Doerr, David R., California’s Tax Machine: A History of Taxing and Spending in the Golden State, California Taxpayers’ Association, Sacramento, California, 2000. Hajnal, Zoltan L., Paul G. Lewis, and Hugh Louch, Municipal Elections in California: Turnout, Timing, and Competition, Public Policy Institute of California, San Francisco, California, 2002. Legislative Analyst’s Office, A New Blueprint for California School Facility Finance, Sacramento, California, 2001. Lewis, Paul G., Deep Roots: Local Government Structure in California, Public Policy Institute of California, San Francisco, California, 1998. Lewis, Paul G., and Elisa Barbour, California Cities and the Local Sales Tax, Public Policy Institute of California, San Francisco, California, 1999. McGuire, Therese J., and Kim S. Rueben, “Tax and Bond Measures in California and Illinois: Observations on Local Governments Operating under State-Imposed Constraints,” Proceedings of the 89th Annual Conference on Taxation, National Tax Association, Washington, D.C., 1997. O’Sullivan, Arthur, Terri A. Sexton, and Steve Sheffrin, Property Taxes & Tax Revolts: The Legacy of Proposition 13, Cambridge University Press, Cambridge, Massachusetts, 1995. Schrag, Peter, Paradise Lost: California’s Experience, America’s Future, The New Press, New York, 1998. 130 Sears, David O., and Jack Citrin, Tax Revolt: Something for Nothing in California, Harvard University Press, Cambridge, Massachusetts, 1985. Sheffrin, Steven M., and Terri Sexton, Proposition 13 in Recession and Recovery, Public Policy Institute of California, San Francisco, California, 1998. Sonstelie, Jon, Eric Brunner, and Ken Ardon, For Better or For Worse? School Finance Reform in California, Public Policy Institute of California, San Francisco, California, 2000. Sonstelie, Jon, and Peter Richardson (eds.), School Finance and California’s Master Plan for Education, Public Policy Institute of California, San Francisco, California, 2001. U.S. Bureau of the Census, Census of Governments: Volume 4, Government Finances (machine-readable data files), Washington, D.C., 1972, 1977, 1982, 1987, 1992, and 1997. U.S. Department of Education, National Center for Education Statistics, School District Data Book (SDDB) (computer file), Washington, D.C., 1990. 131 About the Authors KIM S. RUEBEN Kim S. Rueben is a research fellow at the Public Policy Institute of California, where she studies public finance, state and local government budget decisions, and school resources. Her co-authored publications include Equal Resources, Equal Outcomes? The Distribution of School Resources and Student Achievement in California (2000) and Fiscal Rules and State Borrowing Costs: Evidence from California and Other States (1999). She is currently investigating facilities financing in California school districts. She holds a B.S. in applied math–economics from Brown University, an M.A. in economics from the London School of Economics, and a Ph.D. in economics from the Massachusetts Institute of Technology. PEDRO CERDÁN Pedro Cerdán is a research associate at the Public Policy Institute of California. His research interests include educational issues, economic development, and poverty and inequality. He holds a B.A. in economics, specializing in quantitative methods, from the Universitat Pompeu Fabra, Barcelona, Spain. 133 Related PPIC Publications A California State of Mind: The Conflicted Voter in a Changing World Mark Baldassare Municipal Elections in California: Turnout, Timing, and Competition Zoltan L. Hajnal, Paul G. Lewis, and Hugh Louch California Cities and the Local Sales Tax Paul G. Lewis and Elisa Barbour Has Proposition 13 Delivered? The Changing Tax Burden in California Michael A. Shires, John Ellwood, and Mary Sprague The State-Local Fiscal Relationship in California: A Changing Balance of Power J. Fred Silva and Elisa Barbour PPIC publications may be ordered by phone or from our website (800) 232-5343 [mainland U.S.] (415) 291-4400 [Canada, Hawaii, overseas] www.ppic.org 135" } ["___content":protected]=> string(102) "

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" ["_permalink":protected]=> string(109) "https://www.ppic.org/publication/fiscal-effects-of-voter-approval-requirements-on-local-governments/r_103krr/" ["_next":protected]=> array(0) { } ["_prev":protected]=> array(0) { } ["_css_class":protected]=> NULL ["id"]=> int(8305) ["ID"]=> int(8305) ["post_author"]=> string(1) "1" ["post_content"]=> string(0) "" ["post_date"]=> string(19) "2017-05-20 02:36:26" ["post_excerpt"]=> string(0) "" ["post_parent"]=> int(3480) ["post_status"]=> string(7) "inherit" ["post_title"]=> string(8) "R 103KRR" ["post_type"]=> string(10) "attachment" ["slug"]=> string(8) "r_103krr" ["__type":protected]=> NULL ["_wp_attached_file"]=> string(12) "R_103KRR.pdf" ["wpmf_size"]=> string(7) "1101878" ["wpmf_filetype"]=> string(3) "pdf" ["wpmf_order"]=> string(1) "0" ["searchwp_content"]=> string(222610) "Fiscal Effects of Voter Approval Requirements on Local Governments ••• Kim S. Rueben Pedro Cerdán 2003 PUBLIC POLICY INSTITUTE OF CALIFORNIA Library of Congress Cataloging-in-Publication Data Rueben, Kim S. Fiscal effects of voter approval requirements on local governments / Kim S. Rueben, Pedro Cerdán. p. cm. Includes bibliographical references. ISBN: 1-58213-065-5 1. Local revenue—California. 2. Local elections—California. I. Cerdán, Pedro, 1978- II. Title. HJ9204.R84 2003 336'.014794—dc21 2002154263 Copyright © 2003 by Public Policy Institute of California All rights reserved San Francisco, CA Short sections of text, not to exceed three paragraphs, may be quoted without written permission provided that full attribution is given to the source and the above copyright notice is included. PPIC does not take or support positions on any ballot measure or state and federal legislation nor does it endorse or support any political parties or candidates for public office. Research publications reflect the views of the authors and do not necessarily reflect the views of the staff, officers, or Board of Directors of the Public Policy Institute of California. Foreword Between 1978 and 2000, California voters did not make life easy for local governments. The passage of Proposition 13 in 1978, for example, had a chilling effect on local revenues. Likewise, the passage of Proposition 218, which required that any new general tax or fee measure achieve a two-thirds majority vote, did little to aid local efforts to raise funds. For these governments, the only good news along these lines came in 2000, when the passage of Proposition 39 lowered the supermajority needed for school bond approval to 55 percent. With this recent history in mind, Kim Rueben and Pedro Cerdán have tracked patterns in local fiscal measures between 1986 and 2002. Although their findings certainly do not suggest a profligate electorate, eager to raise taxes for local services, they do reveal broad patterns in the willingness to fund certain services. Their study also explores more specific fiscal questions. Which local governments are more likely to use the ballot box to raise revenues? Which have actually succeeded? What kinds of ballot measures have the highest success rate? In general, the authors found that measures that fund specific services—especially school facilities, transportation, and fire protection—have higher approval rates than those that fund general services. In contrast, proposals to fund parks and libraries are rather less likely to succeed; as a result, these traditional public services are more likely to go unfunded. This report gives us a fresh understanding of how the fiscal limitation movement has affected local public finance in California since the mid1980s. Although the long-term consequences of its findings are not fully understood, the reader is left with two impressions: Local voters are still actively determining their own fiscal fate, and some cities and segments of the state’s population are in danger of being left behind. David W. Lyon President and CEO Public Policy Institute of California iii iv Summary California public finance has become increasingly complicated over the last 25 years. Because local officials now need voter approval to pass a growing set of local taxes, local governments, especially counties and school districts, have become more dependent on state funds to provide local services. As the economy weakens and current public finance instruments raise less money, local governments again face hard decisions about how to pay for needed services—services that the public wants or that local governments are required to provide but that voters do not necessarily want to pay for with new or increased taxes. Limitations on local government revenue sources started with Proposition 13 in 1978, which limited property tax rates and the ability of local governments to increase assessed property values and to pass special taxes. Since then, several initiatives and court decisions have also affected the fiscal authority of local governments, usually increasing the role voters play in determining revenue sources. For example, Proposition 218, passed in 1996, required voter approval for any new general taxes, fees, and assessments. This report examines the ways local jurisdictions (school districts, cities, and other local governments) have used the ballot box to pass new taxes or gain approval for capital bond measures. The findings indicate substantial variation in voter reaction to such fiscal measures, depending on region, timing, the type of measure proposed, and the local service to be funded. This information should prove useful to local officials who must decide whether and how to raise revenues in their jurisdictions. From 1986 to 2000, California voters were asked to pass local tax and bond measures over 2,500 times. About two-thirds of local fiscal measures were for taxes and fees, and they passed at a rate of 42 percent. The other one-third were bond authorization requests, which passed at the slightly higher rate of 48 percent. Most bond measures were proposed and passed by school districts, and school districts primarily v proposed bond measures rather than tax measures. In contrast, other local governments were more likely to propose tax measures. California has experienced an increase in the number of fiscal measures since 1996. This increase is related to increased demand for school infrastructure spending leading to increased rates of school district bond proposals. This trend accelerated in the aftermath of Proposition 39—a state measure passed in 2000 that lowered the supermajority needed to pass school bonds to 55 percent. Tax measures also increased in occurrence and in passage rates, reflecting the need for voter approval for general taxes and certain fees and assessments beginning in 1996. We examine five questions in this report: 1. How have statewide restrictions on local governments influenced the relationship between state and local governments? Specifically, how have they affected which level of government raises funds to provide local services? We find that following the passage of Proposition 13 in 1978, county and school districts became increasingly reliant on other levels of government, most notably the state, to raise funds to provide local services. In California, the amount of money spent by local governments raised by own-source revenue (revenue that is raised and spent by the same level of government) fell from 58 percent in 1977 to 50 percent in 1997. In contrast, local governments in the rest of the country became increasingly reliant on own-source funds, increasing their use from 57 percent to 62 percent. County governments in California went from raising half of all their funds in 1977 to raising only 36 percent of funds from own-source revenues by 1997. In the rest of the country, counties increased their reliance on own-fund sources from 57 to almost 70 percent over the same period. School districts have become increasingly reliant on state funds in both California and the rest of the country, but these changes were more dramatic in California. Cities and special districts in California raise most of their funding through local sources and have consequently been more reliant on local approval of new measures and the use of fees and assessments. vi 2. To what extent have governments used the ballot box to raise new funds? What choices have local governments made in response to statewide restrictions on how revenue is raised and the need for local approval? Local governments have proposed multiple measures to raise revenues including bonds, parcel taxes, business or consumer taxes, hotel room taxes, and sales taxes. An increasing number of local governments used ballot measures to raise new taxes, but most of them did not use the ballot box repeatedly. Although a few local governments, most notably those in the Bay Area, proposed multiple measures, most local governments requested voter approval for new funds only occasionally and stopped after one successful election. School districts were most likely to propose bond measures, although most districts that proposed bond measures passed only one. More school districts proposed and passed bonds following the passage of Proposition 39, which lowered the supermajority required for passage from two-thirds to 55 percent. Cities were most likely to propose tax measures, although almost half of all cities proposed no measures and only one-third of cities successfully passed a ballot measure. Use of ballot measures increased for cities and counties after 1996 and the explicit requirement of voter approval for general taxes. We find that passage rates depended on which services were to be funded, with transportation and emergency service measures passing most often and recreation and park measures passing least often. We also find distinct regional patterns. Governments in the Bay Area and the southern regions of the state proposed measures most often, and the Bay Area measures passed at a higher rate than measures elsewhere. Finally, measures proposed by special districts passed at a higher rate than city or county measures—even when they funded the same function. 3. In the case of school districts, how do restrictions on funding sources interact with legal requirements for spending equity? Does the use of local ballot measures lead to differences in current or capital expenditures? vii School districts are highly reliant on local bond measures to fund infrastructure spending. About one-third of school construction and modernization funds came from bond measures. Most school districts passed only one bond measure and often returned to the ballot box until successful. Support for school bond elections has been growing in recent years, with a higher percentage of school bonds being proposed and passing even before the passage of Proposition 39 (Figure S.1). Following Proposition 39, 32 school districts proposed bond measures in November 2001, of which 29 passed. In March 2002, 67 out of 76 bond measures passed, and in November 2002, 103 bond measures were proposed and 84 passed. In the late 1990s, the amount of money raised to pay for school facility construction was strongly related to both enrollment and assessed valuations; districts with higher assessed value raised more money. Constitutional limits on the amount of debt school districts can incur are directly based on assessed value within a district. Thus, wealthier 120 100 80 60 40 20 0 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 NOTES: Each period is one-third of a year. The year labels correspond to the third period, including the November general election. Figure S.1—Number of Bond Measures Proposed by School Districts, 1986–2002 viii Number of measures districts can raise more money if a bond measure is successful. Furthermore, matching programs for state funds have exacerbated differences in spending levels across school districts. Indeed, as voters recently approved $13.05 billion in state bond funds for education facilities by passing Proposition 47 and the state is proposing another $12.25 billion in 2004, it may be important to reexamine how state funds are allocated. Capital expenditures are not subject to equity requirements as set forth under court decisions about school finance equalization, but may be called into question in current court cases. School districts can propose parcel taxes to raise more money for current expenditures. These taxes raise a given amount of money per property and are not based on assessed value. Tax measures were proposed much less frequently by school districts and were approved in only 55 school districts. They usually were for less than $200 per parcel and lasted for a limited period of time. School districts that have passed a parcel tax measure will often approve another measure as the first tax expires. Parcel taxes were most often proposed by Bay Area school districts; they were also used by small school districts with high-income households and high property values. Districts that successfully passed a parcel tax spent approximately $600 (about 8 percent of current expenditures) more per student in 1999–2000 than other school districts (about 60 percent of this spending difference was directly related to parcel taxes). Although these differences in spending levels were not directly related to assessed value differences in districts, wealthier districts were more likely to pass these measures. 4. What characteristics differentiate municipalities that have succeeded in passing fiscal measures from those that have not? Can we explain spending disparities by the passage of new taxes, or do they reflect underlying differences in cities? Municipal governments have become less reliant on the property tax, but overall revenues have not declined for two groups of cities: those that never proposed ballot measures and those that successfully passed a ballot measure. When we examine which cities went to the ballot box and which cities approved new tax measures, we find that cities that relied more on property taxes historically were more likely to ask for and ix receive authorization to implement new tax measures. We also find that proposal and passage rates were higher in cities with a high percentage of registered Democrats. Larger cities and cities in the Bay Area were also more likely to ask for and receive voter approval for new tax measures. On average, cities that proposed a ballot measure but were unsuccessful at passing a new tax had lower revenues before Proposition 13 passed, and those revenue-level differences widened over time. When we compare the three sets of California cities—those that never proposed tax measures, those that passed new tax measures, and those that proposed but failed to pass tax measures—we find different fiscal outcomes. Figure S.2 shows per capita average revenue for each type of city. We find that these disparities are partly related to the direct effect of passing ballot measures, but they are also related to differences in the characteristics of these groups of cities. Most notably, cities that were unsuccessful had historically raised less revenue, especially from assessments and fees, had a lower percentage of voters registered as Democrats, and had lower household income than those that successfully passed a tax measure. 1,200 1,000 Did not propose Proposed and did not pass Proposed and passed Revenue dollars (2000) 800 600 400 200 0 1987 1992 1997 Figure S.2—Average Per Capita General Revenue, by Measure Outcome, 1987, 1992, and 1997 x We also find that the relationship between city population demographics and the level of revenues raised has changed over time. City government funds have become increasingly dependent on household mobility, with cities having fewer families living in the same house as five years earlier on average raising more money, because of more frequent reassessment of property to market value. This revenue difference results because of Proposition 13, which limits reassessments to when property is sold. Therefore, of two cities with the same market value for property and given increasing housing prices, the city with more frequent turnover will have higher property tax revenues because assessed values will be closer to market values. 5. Are certain levels of government better able to pass new measures? What kinds of taxes tend to pass once they are placed on the ballot and do other characteristics of the elections affect passage rates? We find differences in passage rates across types of governments, even when timing, type of tax proposed, use of tax, and regions are controlled for. Controlling for all other factors, county tax measures passed 32 percent of the time, city measures passed 40 percent of the time, and special district elections passed 47 percent of the time. This pattern may be due to the more specific targets of special district elections. Certain uses of funds and certain types of taxes have higher passage rates all else equal. Transportation measures passed 56 percent of the time, whereas park measures passed an estimated 29 percent of the time. Similarly, after controlling for other characteristics, we find that hotel taxes and other business taxes passed 56 percent of the time and consumer taxes passed 36 percent of the time. Our findings suggest that if popular programs such as transportation measures or fire protection require funding, a dedicated tax, despite the required supermajority for approval, is more likely to garner voter support than a general tax. There are limitations to proposing special taxes, as these funds are earmarked for specific spending areas and therefore will reduce local officials’ flexibility. When controlling for changes in what is placed on the ballot, passage rates have not changed significantly since 1996. Although more xi measures have been proposed, these new measures are not any more or less likely to pass. This result is due to the lower passage rate required (a simple majority) being offset by higher voter preference for funding some specific and more popular functions. We also find that tax measures are more likely to pass if proposed in off-cycle elections. There has been a growing use of ballot measures following passage of Proposition 218 in 1996, which codified the requirement for voter approval for all general taxes. Although voters are playing an increasingly important role in the fiscal decisionmaking process, they are willing to approve new funding sources. Voters are more likely to pass tax measures proposed by special districts and cities than by counties. In general, voters appear more willing to support specific services or construction that they feel will be of direct use to them. Thus, it is important for officials to specify the use of new funds when writing ballot measures. However, voter preferences may leave some traditional government services inadequately funded. For example, transportation and fire services usually receive voter support, but passage is spotty for library services or parks. For cities and counties interested in raising general funds, the type of tax proposed also affects passage rates. The general tax instruments with the highest chance of passage are those that homeowners do not pay directly (i.e., hotel taxes or business taxes). The history of statewide initiatives also illustrates that voters become concerned when they feel that local governments are circumventing voters’ advisory role. For example, the growing use of fees and miscellaneous charges led to Proposition 218, which returned to voters the final authority on these revenue sources. xii Contents Foreword..................................... iii Summary..................................... v Figures ...................................... xv Tables ....................................... xvii Acknowledgments ............................... xxi 1. INTRODUCTION ........................... 1 2. HISTORY OF LOCAL REVENUE RESTRICTIONS .... A Brief History of Local Tax Reform and Restrictions...... Local Fiscal Measures in California.................. California and U.S. Local Government Finances ......... 5 5 11 13 3. SCHOOL DISTRICT ELECTIONS AND THEIR EFFECT ON REVENUES ...................... School District Bond Elections .................... Bond Measures Since the Passage of Proposition 39 ..... Regional Patterns in Bond Elections ............... Distribution of Bond Measures Across School Districts ... Determinants of School District Bond Elections and Capital Expenditures ....................... School District Parcel Tax Elections ................. Regional Patterns in Parcel Tax Elections ............ Distribution of Tax Measures Across School Districts .... Determinants of School District Tax Elections and Current Revenues ......................... Summary .................................. 19 19 21 23 26 28 36 39 40 42 44 4. CITY FISCAL MEASURE ELECTIONS AND THEIR EFFECT ON REVENUES ...................... Municipal Bond Elections ....................... Regional Patterns in Bond Elections ............... Distribution of Bond Measures Across Municipalities .... 47 48 50 51 xiii Determinants of Municipal Government Bond Elections and Capital Revenues ....................... Municipal Tax Elections ........................ Tax Measures Since Passage of Proposition 218 ........ Regional Patterns in Municipal Tax Elections ......... Distribution of Tax Measures Across Municipalities ..... Determinants of Municipal Tax Elections and Current Revenues ............................... Summary .................................. 5. COUNTY AND SPECIAL DISTRICT USE OF THE BALLOT BOX .............................. County Use of the Ballot Box ..................... County Bond Elections ....................... County Tax Elections ........................ Regional Patterns in County Tax Measures ........... Special District Use of the Ballot Box ................ Bond Elections Held by Special Districts ............ Regional Patterns in Special District Bond Elections ..... Tax Elections Held by Special Districts ............. Regional Patterns in Special District Tax Elections ...... Ballot Use Across Different Types of Governments ....... Summary .................................. 6. POLICY CONSIDERATIONS ................... 52 53 56 57 58 59 68 69 69 71 71 74 76 76 77 78 80 83 90 93 Appendix A. Information on Local Measures .................... 97 B. Fiscal Information ............................ 103 C. School District Information ...................... 107 D. Municipal Election Information ................... 115 E. County and Special District Election Information ........ 121 Bibliography .................................. 129 About the Authors ............................... 133 Related PPIC Publications .......................... 135 xiv Figures S.1. Number of Bond Measures Proposed by School Districts, 1986–2002........................ viii S.2. Average Per Capita General Revenue, by Measure Outcome, 1987, 1992, and 1997 ................ x 2.1. Real Per Capita General Revenue, All Local Governments ............................. 15 2.2. Real Per Capita Own-Source General Revenue, All Local Governments ............................. 15 3.1. Number of Bond Measures Proposed by School Districts, 1986–2002........................ 20 3.2. Passage Rate of Bond Measures Proposed by School Districts, 1986–2002........................ 21 3.3. Number of Bond Measures Proposed by School Districts, 1986–2000........................ 24 3.4. Passage Rate of Bond Measures Proposed by School Districts, 1986–2000........................ 25 3.5. Average Total Capital Revenue and Bond Revenue per Student, 1992–2000 ........................ 32 3.6. Number of Parcel Tax Measures Proposed by School Districts, 1986–2002........................ 38 3.7. Passage Rate of Parcel Tax Measures Proposed by School Districts, 1986–2002........................ 38 3.8. Number of Parcel Tax Measures, by School District, 1986–2000 .............................. 40 4.1. Number of Bond Measures Proposed by Municipal Governments, 1986–2000 .................... 49 4.2. Passage Rate of Bond Measures Proposed by Municipal Governments, 1986–2000 .................... 50 4.3. Number of Fiscal Measures, by Type.............. 54 4.4. Passage Rate of Fiscal Measures, by Type ........... 56 4.5. Average Per Capita General Revenue, by Measure Outcome, 1972–1997 ....................... 61 xv 4.6. Estimated Probability of Proposing and Passing a Tax Measure, by Region ........................ 66 4.7. Estimated Real Per Capita General Revenue for a City with Average Demographics ................... 67 5.1. Percentage of 1997 Direct Expenditures Controlled by Counties ............................... 70 5.2. Countywide Measures, by Type of Tax ............ 73 5.3. Passage Rate of Countywide Measures, by Type of Tax ................................... 74 5.4. Number of Special Districts, 1997 ............... 77 5.5. Number of Tax Measures Proposed by Special Districts ................................ 81 5.6. Passage Rate of Tax Measures Proposed by Special Districts, Total............................ 82 5.7. Number of Total Tax Measures Proposed, by County ... 85 5.8. Passage Rate of Tax Measures Proposed, by County .... 86 B.1. Real Per Capita General Revenue for Cities, 1972–1997 .............................. 105 xvi Tables 2.1. Ballot Measure Requirements for Local Revenues in California ............................... 2.2. Per Capita Revenue in California and the Rest of the United States ............................. 3.1. Distribution of Bond Measures Proposed and Passed by School Districts, by Type, 1986–2000 ........... 3.2. Number of Bond Measures Proposed and Passed by School Districts Since Passage of Proposition 39 ...... 3.3. Number of Bond Measures Proposed and Passed, by Region, 1986–2002 ........................ 3.4. Distribution of Bond Measures Proposed by School Districts, 1986–2000........................ 3.5. Distribution of Bond Measures Passed by School Districts, 1986–2000........................ 3.6. Demographic Characteristics of School Districts, by Bond Measure Experience .................... 3.7. School District Per Pupil Capital Revenue, by Bond Measure Experience ........................ 3.8. Estimated Change in Probability of Proposing and Passing Bond Measures ...................... 3.9. Distribution of Parcel Tax Measures Proposed and Passed by School Districts, by Type, 1986–2000 ...... 3.10. Distribution of Parcel Tax Measures Proposed and Passed by School Districts, by Region, 1986–2000 ..... 3.11. Distribution of Parcel Tax Measures Proposed by School Districts, 1986–2000 ................... 3.12. Distribution of Parcel Tax Measures Passed by School Districts, 1986–2000........................ 3.13. Demographic Characteristics of School Districts, by Parcel Tax Experience, 1986–2000 ............... 3.14. Fiscal Characteristics of School Districts, by Parcel Tax Experience, 1986–2000 ...................... 12 16 20 22 23 26 27 30 32 34 37 39 41 41 43 44 xvii 4.1. Number of Bond Measures Proposed and Passed, by Function, 1986–2000 ....................... 4.2. Number of Bond Measures Proposed and Passed, by Timing, 1986–2000 ........................ 4.3. Number of Bond Measures Proposed and Passed, by Region, 1986–2000 ........................ 4.4. Distribution of Bond Measures Proposed by Cities, 1986–2000 .............................. 4.5. Distribution of Bond Measures Passed by Cities, 1986– 2000 .................................. 4.6. Demographic and Fiscal Characteristics of Cities, by Bond Measure Experience, 1986–2000 ............ 4.7. Number of Tax Measures Proposed and Passed, by Function, 1986–2000 ....................... 4.8. Number of Tax Measures Proposed and Passed, by Timing................................. 4.9. Number of Tax Measures Proposed and Passed, by Region, 1986–2000 ........................ 4.10. Distribution of Tax Measures Proposed by Municipal Governments, 1986–2000 .................... 4.11. Distribution of Tax Measures Passed by Municipal Governments, 1986–2000 .................... 4.12. Demographic Characteristics of Cities, by Tax Measure Experience, 1986–2000 ...................... 4.13. Fiscal Characteristics of Cities, by Tax Measure Experience, 1986–2000 ...................... 4.14. Estimated Change in Probability of Proposing and Passing Tax Measures ....................... 5.1. Number of Bond Measures Proposed and Passed by Counties, by Function, 1986–2000 .............. 5.2. Number of Bond Measures Proposed and Passed by Counties, by Region, 1986–2000 ................ 5.3. Number of Tax Measures Proposed and Passed by Counties, by Function, 1986–2000 .............. 5.4. Number of Tax Measures Proposed and Passed by Counties, by Timing ........................ 5.5. Number of Tax Measures Proposed by Counties, by Region and Function ........................ 48 50 51 51 52 53 54 57 58 59 59 60 62 64 71 72 72 74 75 xviii 5.6. Passage Rates of Tax Measures, by Region and Function ............................... 75 5.7. Number of Bond Measures Proposed and Passed, by Type of Jurisdiction ........................ 78 5.8. Number of Bond Measures Proposed and Passed by Special Districts, by Timing ................... 78 5.9. Number of Bond Measures Proposed and Passed by Special Districts, by Region ................... 79 5.10. Number of Tax Measures Proposed and Passed, by Type of Jurisdiction ............................ 79 5.11. Number of Tax Measures Proposed and Passed by Special Districts, by Timing ................... 80 5.12. Number of Tax Measures Proposed, by Region and Type of Special District .......................... 82 5.13. Passage Rates of Tax Measures, by Region and Type of Special District............................ 83 5.14. Number of Measures Proposed and Passed, by Region... 84 5.15. Number of Bond and Tax Measures Proposed and Passed, by Function ........................ 87 5.16. Number of Bond and Tax Measures Proposed and Passed, by Timing.......................... 88 5.17. Estimated Change in Probability of Passing Tax Measures ............................... 89 A.1. Number of Measures, by Source and Type .......... 98 A.2. Number of Measures, by Source, Type, and Year ...... 99 A.3. Number of Measures, by Source, Type, and Year, Excluding School District Elections .............. 100 A.4. Number of Cities, by Election Cycle Timing ........ 101 A.5. School District Elections, by Type of Measure and Timing................................. 102 B.1. Comparison of Cities in and out of Sample ......... 104 C.1. Number of School Districts and Number of Bond Measures Proposed and Passed, by County, 1986–2002 .............................. 108 C.2. Determinants of Bond Measure Proposals and Passage Rates, Regression Results ..................... 110 C.3. Distribution of Key Regression Variables ........... 111 xix C.4. Determinants of Per Pupil Capital Revenue, 1992– 2000 .................................. 112 C.5. Number of Parcel Tax Measures Proposed and Passed by School Districts, by County, 1986–2000 ........... 113 D.1. Number of Tax Measures Proposed and Passed by Cities, 1986–2000 .............................. 116 D.2. Determinants of Tax Measure Proposals and Passage Rates, Regression Results ..................... 118 D.3. Distribution of Key Regression Variables ........... 120 D.4. Demand for City Revenues, Controlling for Which Cities Proposed and Passed Tax Measures........... 120 E.1. Percentage of Direct Expenditures Controlled by Counties, Number of Special Districts, and Number of Tax Measures Proposed and Passed by Special Districts, 1986–2000 .............................. 122 E.2. Number of Tax Measures Proposed and Passed by Non– School District Local Governments, by County, 1986– 2000 .................................. 124 E.3. Determinants of Number of Measures Proposed and Passed by Counties, 1986–2000 ................. 126 E.4. Determinants of the Probability of a Tax Measure Passing................................. 127 xx Acknowledgments We would like to thank Mark Baldassare, Gary Hart, Paul Lewis, John Mockler, Joyce Peterson, Steven Sheffrin, Fred Silva, and Jon Sonstelie for their thoughtful reviews of this manuscript. We would also like to express our appreciation to the California Realtors Association, CASH, and CDIAC for providing us with data on tax and bond measures, with a special thanks to Hardy Gumnor for being especially helpful. We would also like to thank Mary Sprague, Elizabeth Berko, and Sun Kim for help in compiling and organizing the local measure data and Marianne Bitler, Elisa Barbour, Cynthia Gustafson, and Tracy Gordon for help in organizing and accessing the Census of Governments data. This work relies on two companion studies: Therese McGuire collaborated on an earlier article about local tax measures and cities and Edmund Balsdon and Eric Brunner collaborated on work related to school district bond elections. Patricia Bedrosian and Peter Richardson assisted with editorial comments. Abby Cook and Victoria Pike Bond helped with media outreach and meetings with local officials. Our other colleagues at PPIC also provided valuable comments on earlier drafts and at seminars about this topic. Deborah Reed was instrumental in helping us complete a first draft of this report. The report also benefited from meetings with local government officials, especially at the County Auditors conference in 2002. Although this report reflects the contributions of many people, the authors are solely responsible for its content. Any opinions or interpretations expressed are those of the authors and do not necessarily reflect the views of the Public Policy Institute of California. xxi 1. Introduction The passage of Proposition 13 in 1978 marked the beginning of a sea change in the fiscal powers and responsibilities of local governments in California, moving greater control over local government finances to the ballot box through direct voter control.1 In addition to severely limiting property taxes, Proposition 13 also required voter approval for special taxes. In the 25 years that followed, subsequent statewide initiatives extended the voter approval requirement to additional categories of taxes and charges and recently changed the requirements for approval of bond measures. These initiatives were designed to give voters a larger voice in the spending and revenue decisions of cities, counties, school districts, and special districts. The initiatives’ proponents envisioned a choice between seeking voter approval and curtailing spending. In practice, however, using the ballot box to raise revenues is only one possible response of local governments to voter approval requirements. Another is for the state government to play a larger role in raising funds to provide local services. Local officials could also turn to revenue sources that do not require voter approval. When Proposition 13 required approval for special taxes, local governments increased their reliance on general taxes, fees, and assessments. Subsequent statewide initiatives then sought to require voter approval for these alternative funding sources. Much attention has been paid to history surrounding the passage of Proposition 13, its effect on overall government spending in California, and its influence on property values in California.2 However, little of ____________ 1We use local government to refer to nonstate and nonfederal levels of government—counties, cities, special districts, and school districts. 2See, for example, Sears and Citrin (1985), O’Sullivan, Sexton, and Sheffrin (1995), Schrag (1998), and Doerr (2000). These authors occupy many positions on the political spectrum and give different interpretations of circumstances leading up to Proposition 13 and its consequences. 1 this work has examined differences across local governments caused by the provisions in Proposition 13 and subsequent initiatives that expanded voters’ control over revenue sources. To investigate the interaction of voter approval requirements and the fiscal pressures facing local governments, this report studies school districts and city governments— the levels of local governments the electorate is most likely to interact with, where basic government services including public education and police and fire protection are typically provided. School districts usually used the ballot box to pass bond measures to pay for school facilities. This reflects the shifting control of current school spending to the state level following court cases requiring spending equity, whereas capital expenditures (which are funded largely through bonds) remain primarily a local responsibility. However, calls for spending equality in facilities may add another level of complication for school districts. Cities are heavily dependent on local taxes and have used the ballot box far more frequently to propose new tax measures.3 Expanding on the existing literature on Proposition 13, this report examines the proposition’s overall effect on local revenues. It then evaluates the tradeoffs facing local governments between using the ballot box to raise revenues, restricting revenue levels, and finding alternative funding strategies. Although we focus on school districts and cities, we also briefly discuss the use of alternative measures by counties and special districts. We seek to answer five basic questions: 1. How have statewide restrictions on local governments influenced the relationship between state and local governments? Specifically, how have they affected which level of government raises funds to provide local services? 2. To what extent have governments used the ballot box to raise new funds? What choices have local governments made in response to statewide restrictions on how revenue is raised and the need for local approval? ____________ 3In contrast, county governments serve many functions including acting as an agent of the state by providing certain services (such as public assistance or court functions) and municipal services in unincorporated areas. Because of these varying roles, we limit our comparisons of counties but we do discuss county elections in Chapter 5. 2 3. In the case of school districts, how do restrictions on funding sources interact with legal requirements for spending equity? Does the use of local ballot measures lead to differences in current or capital expenditures? 4. What characteristics differentiate municipalities that have succeeded in passing fiscal measures from those that have not? Can we explain spending disparities by the passage of new taxes, or do they reflect underlying differences in cities? 5. Are certain levels of governments better able to pass new measures? What kinds of taxes tend to pass once they are placed on the ballot and do other characteristics of the elections affect passage rates? The report is organized as follows: Chapter 2 examines the legislative and initiative history surrounding local governments’ ability to raise funds and describes aggregate uses of ballot measures. We also compare California’s local government revenue levels to those in the rest of the country and examine aggregate changes in funding responsibility before and after the passage of Proposition 13. Chapter 3 focuses on school districts, exploring school bond and parcel tax measures and their influence on revenue levels. Chapter 4 focuses on cities, briefly analyzing the use of bond measures but mainly exploring the use of tax measures and the types of funds used to provide local services. Chapter 5 expands our analysis to consider tax and bond measures for counties and special districts. Examining the role of other governments is particularly important in California because of the differential reliance on special districts and county governments. We then explore how these differences affect the use of the ballot box, examining overall regional patterns and exploring which services are more likely to gain voter approval for new taxes. Finally, Chapter 6 explores the ramifications of the growing need for voter approval to fund public services. 3 2. History of Local Revenue Restrictions Local governments in California face a complicated set of restrictions on their ability to raise funds and provide services to their residents. In this chapter, we provide a brief history of local finance sources and discuss how these sources have been authorized and limited over time by both the legislature and voters. We are concerned with state-level restrictions (often initiatives placed on the ballot by voters) that require local voter approval before local governments can collect certain revenues. We refer to such ballot measures as local measures. We first describe these statewide restrictions and then discuss our set of local fiscal measures. Finally, we present some evidence on the aggregate changes in local revenue sources. The cumulative effect of these restrictions has been twofold: Most new local efforts to raise revenue require voter approval, and some types of local governments increasingly rely on the state for funding. A Brief History of Local Tax Reform and Restrictions The first constraint on local government revenue appeared in the state constitution in 1879 and required the approval of two-thirds of voters for any general obligation debt for any local agency. As part of constitutional reform in 1911, California adopted practices that allowed for direct legislation by permitting state and local initiatives and referenda. Voters have used these direct democracy instruments in more recent years to approve several statewide initiatives that limit local governments’ ability to impose taxes or fees for local purposes, to authorize local general obligation debt, or to lower the passage requirement for school district bonds. 5 In 1978, Proposition 13 became the most consequential tax limit passed as of that time, but it was not voter groups’ and public officials’ first attempt to limit taxes. Increasing assessed values for property, increased state surpluses, and a court mandate to equalize school district spending across the state all contributed to the passage of Proposition 13. Tax reform proposals appeared throughout the 1960s and 1970s both as ballot measures and as tax plans proposed by the assembly and the governor.1 Often, these proposals were very complicated and hard for voters or legislators to understand. In addition, some were defeated because of uncertainty as to where replacement funds would come from. Doerr (2000) provides a thorough description of these early ballot measures. In 1972, a successful tax reform bill (SB 90) was supposed to provide property tax relief to homeowners and satisfy court rulings concerning education finance equity. The relevant provisions of SB 90 for local governments were property tax rate limits for cities, counties, and special districts and revenue limits for school districts. State aid was increased to school districts to equalize school district spending and to decrease school district reliance on the property tax. This last provision was in part a response to the Serrano v. Priest lawsuit that was winding its way through the courts. The Serrano court case and rulings found that differences in school spending related to differences in assessed values of property were unconstitutional.2 SB 90 also increased homeowners’ exemption levels, provided some tax relief to renters, and increased the state sales tax by 1 percentage point to help pay for these changes. However, SB 90 did not place any limits on how often property would be reassessed. Property tax bills reflect both the tax rates imposed and the level of assessment, so if property values increased and were reassessed relatively often, property tax bills would increase unless property tax rates were lowered. ____________ 1At least four prior initiatives were placed on the ballot, including three sponsored by Howard Jarvis or Paul Gann, the co-sponsors of Proposition 13, and Proposition 1, sponsored by then-Governor Ronald Reagan. 2See Sonstelie, Brunner, and Ardon (2000) for a discussion of school finance reform following the Serrano decision. 6 In the period leading up to 1978, property values and property tax bills were rising quickly.3 At the same time, California’s state government had a large and growing surplus resulting from a combination of increases in inflation and a lack of income tax indexing.4 Thus, when Proposition 13 was placed on the ballot, voters were paying higher property tax bills and the state had an estimated $5 billion surplus that could be used to compensate for revenue losses associated with cuts in property tax rates. In the period leading up to passage of Proposition 13, separate reform bills were going through the two houses of the legislature. However, in 1977 legislators in the two houses and the governor could not agree on a specific tax relief plan. Once Proposition 13 qualified for the ballot, the governor and the legislature proposed a competing measure. Proposition 8 was less straightforward than Proposition 13 and did not offer property tax relief to all homeowners. Following an ill-timed mailing of property tax bills including large increases in property values in Los Angeles, Proposition 13 passed by nearly a 2-1 margin.5 Proposition 13 required a two-thirds vote for any increase in property taxes up to 1 percent of assessed value. It restricted the overall property tax to a maximum of 1 percent of assessed value plus an adjustment for servicing outstanding debt. Proposition 13 also required a two-thirds vote for any increase in taxes for special-purpose use. In ____________ 3State legislation was passed mandating property reassessment to market rates on a timely (often three-year) basis—with assessments being a consistent percentage of market rates. This was in response to a series of scandals uncovered by the San Francisco Chronicle concerning assessors who were accepting payoffs for lower assessments. See Doerr (2000) for more details about this controversy. 4California had a very progressive income tax structure, which meant that as individuals and businesses earned higher income, a larger percentage of funds were necessary to pay state taxes. However, the rise in income taxes in the late 1970s mainly resulted from rising inflation rates, so although nominal incomes were rising, the real amount a family could buy with a given amount of money was not and the lack of indexing led to a real increase in the amount of taxes paid. Thus, families were able to afford fewer things even with higher income levels. The lack of indexing was common across most states and in the federal government—indexing of tax schedules was introduced in California in 1978. 5Doerr (2000) and Schrag (1998) provide detailed accounts of the debate leading up to Proposition 13. They provide very different perspectives on the period and mainly focus on statewide effects. 7 addition, it rolled back assessed property valuations to their 1975 levels, allowing only a 2 percent annual increase in assessed valuation until a property is sold, at which point it is reassessed to market value. After passage of Proposition 13, the state legislature had to decide how to distribute the newly restricted funds and pass implementing legislation. The state’s plan effectively consolidated revenues at the county level and distributed them to local governments in proportion to their funds in 1975–1976. The state also replaced school district funds and then reallocated the revenue from property taxes earmarked for schools to other county governments until 1991. The property tax, which had been the main source of local revenues, effectively became a state-controlled tax in California. Thus, the distribution of property tax revenues is based essentially on the one in place in 1975. Therefore, although the state has changed dramatically over the last 25 years— increasing in both population and diversity—the distribution of property tax revenues within a county has not changed substantially. Proposition 13 did allow property tax rates to exceed 1 percent to pay for existing debt service, although the proposition was not clear on whether the exception could be applied to debt incurred after 1978. Proposition 46, passed in June 1986, allowed voters to increase the property tax above the 1 percent maximum for a limited amount of time to pay for debt service on new general obligation bonds passed with the approval of a two-thirds majority vote. Thus, from 1978 to 1986, local governments were not sure how they would pay back new debt and thus curtailed infrastructure projects that would have been funded with bond revenues. Court cases in the early 1980s also raised questions as to what types of governments were restricted by Proposition 13 and what kinds of taxes required voter approval. For example, were special districts not dependent on the property tax covered by Proposition 13? Did they require voter approval for new revenues? Were new general purpose local taxes covered? The responses to these questions and the increase in alternative funding sources led Howard Jarvis to place another initiative on the ballot in 1984 (Proposition 36) that was defeated by voters. Proposition 36, called the “Save Prop. 13” initiative, would have limited non–ad valorem taxes, required any local tax to be approved by a two- 8 thirds vote of the people, and limited governments’ use of fees.6 This was followed by Proposition 62, which was passed in 1986. Proposition 62 prevented the imposition of new general taxes by local agencies without (majority) voter approval. Unlike Proposition 13, which changed the state constitution, Proposition 62 was a statutory initiative. Its statutory nature led to challenges by charter cities who claimed, and courts upheld, that a charter city’s right to impose general taxes was protected by the home rule powers granted in the state constitution and could not be limited by a statutory measure. The validity of Proposition 62 was also challenged by noncharter localities. In 1995, the California Supreme Court reversed earlier lower court decisions and found Proposition 62 to be constitutional and valid for noncharter local governments. The debate about the application of Proposition 62 as a statutory initiative also ended with the passage of Proposition 218 in 1996. Proposition 218, proposed by the Howard Jarvis Taxpayers Association, amended the state constitution to require that a majority of voters approve any increase in general taxes. In addition, Proposition 218 required property-related assessments, fees, and charges to be submitted either to property owners for majority approval or to voters for twothirds majority approval. This latter requirement addressed the criticism that tax restrictions had led to a renaming of taxes as fees and assessments, which did not require voter approval. Proposition 62 and Proposition 218 covered general taxes and required a simple majority vote, whereas Proposition 13 referred to “special” taxes and required a two-thirds majority vote. Special taxes are those imposed by a city, county, school district, or special district to fund a specific service; general taxes are those raised to fund general government services. What constitutes a special tax has also been the subject of litigation, and the courts have made ambiguous and sometimes contradictory decisions, especially concerning taxes proposed by special districts, which are created to provide a specific service but are typically funded from general funds. Court cases have found that any tax passed ____________ 6For a complete description of the restrictions on local governments that would have been imposed by Proposition 36, see Doerr (2000). 9 by a special district is a special tax and requires a two-thirds majority vote. New court challenges are currently under way concerning which fees and assessments are covered under Proposition 218. Finally, Proposition 37, an initiative proposed but not passed on the November 2000 ballot, explicitly specified which fees and assessments would need voter approval. Other legislative actions that have affected local revenue sources include the Mello-Roos Act of 1982, which provided for the creation of community facilities districts (CFDs). These districts allow for specific services for individuals and properties within the district, and taxes (almost always parcel taxes or fees and assessments) are levied to pay for these services. The state legislature also allowed a local sales tax at a uniform rate of 1 percent, a 0.25 percent county transportation tax rate, and local add-on rates for specific purposes—with voter approval—that are not to exceed an additional 1 percent.7 Because several special funding regulations apply specifically to school districts, we will review the voter requirements and limits for school districts. Following the passage of Proposition 13, and until 1986, school districts were unable to pass local bond measures and relied primarily on state money to fund school construction and modernization. Proposition 46, passed in 1986, reestablished the authority of school districts (along with other local governments) to issue general obligation bonds subject to the approval of two-thirds of voters in the district. In 1986, the state legislature authorized school districts to directly impose developer fees to finance new school construction.8 Before 1986, school districts had no independent authority to impose developer fees and were reliant on city or county officials. School districts were able to form CFDs under the Mello-Roos Act of 1982, which allowed school districts to create smaller areas over which fees could be assessed to pay for new school construction. Proposition 39, ____________ 7For more information on local government tax powers, see California Senate Committee on Local Governments (1996). 8Fees can be imposed only on new developments. The maximum fee is $1.50 per square foot for residential development and $0.25 per square foot for commercial and industrial development. 10 passed in 2000, lowered the voter approval threshold for facilities financing from two-thirds to 55 percent.9 Finally, in addition to the direct restrictions on both tax and bond financing, California voters have restricted the growth rate in expenditures for both state and local governments. Proposition 4, also known as the Gann Initiative, was passed in 1979 and constitutionally restricted the growth rate of expenditures of each level of government to the growth rate in state population and inflation. If revenues exceed this level, the government is required to rebate the excess. However, voters can agree to override the expenditure limit with a simple majority approval. In this report, we do not cover expenditure limit override measures because of limited information on this type of local ballot measure. We do have information on the use of expenditure override measures from 1987 to 1992. Over this period, 161 measures were proposed and 142 overrides passed. Thus, if existing tax instruments raise more money than raised in prior years because of changes in economic circumstance, voters appear to be willing to let local governments keep these funds. The combination of initiatives, constitutional requirements, court decisions, and legislation has led to differences in the level of voter majority that is required for passage of different types of fiscal measures. Table 2.1 summarizes the restrictions in place in California and the margin needed to pass new taxes and bonds. Local Fiscal Measures in California Although ballot measures are playing a growing role in the functioning of local governments in California, there is no single, comprehensive source of information on them. We have compiled information on local ballot measures that relate to new taxes and new bonds from November 1986 to November 2000. Our sources include the California Association of Realtors, the California Debt and ____________ 9Proposition 39 placed additional accountability requirements on school districts that took advantage of this lower passage rate requirement. In addition, this lower passage rate requirement is allowed only during primary or general elections held to elect officials and sets a maximum on the amount that can be approved at any single election. 11 Table 2.1 Ballot Measure Requirements for Local Revenues in California State Constitution (1879) Two-thirds voter approval to issue general obligation debt Proposition 13 (1978) Two-thirds voter approval needed to increase property taxes to 1 percent Maximum property tax of 1 percent except for outstanding debt in 1978; may temporarily exceed maximum for new debt after Proposition 46 (1986) Two-thirds voter approval to impose or increase taxes for special-purpose use Proposition 4, the Gann Initiative (1979) Majority voter approval to allow revenue growth to exceed a limit defined by the growth of state population and state personal income Propositions 62 (1986, effective 1996) and 218 (1996) Majority voter approval to increase taxes or to impose new taxes for general-purpose use Majority property owner or two-thirds voter approval to impose or increase property- related assessments and fees Proposition 39 (2000) 55 percent voter approval for school district bonds subject to election timing restrictions and accountability decisions Investment Advisory Commission, the California Association for Adequate School Housing (CASH), Internet searches of local newspaper stories and websites, and communication with county offices. Appendix A provides a more complete description of these sources of ballot measure data. Our data are comprehensive for school districts but potentially incomplete for city, special district, and county elections during the 1993, 1995, and 1997 election years and for off-cycle elections. On-cycle elections are those held concurrently with statewide general or primary elections. These occur in even years when there are gubernatorial or presidential elections.10 Our analysis suggests that tax measures are less likely to arise in off-year and off-cycle elections. ____________ 10For a discussion of the role that election timing plays in city elections, see Hajnal et al. (2002). 12 Indeed, we find that cities with off-cycle mayoral elections are no more likely to be categorized as never having a tax measure proposed than cities that have their elected positions filled during on-cycle elections. In addition, we have collected preliminary information on school bond elections in 2001 and 2002. We use these data to describe the importance of measures as a fiscal tool of local governments. Because of a lack of information, we cannot describe the use of ballot measures immediately before and after Proposition 13.11 Our sample allows us to illustrate changes in the relative importance of the more recent restrictions, including the initial responses of local governments to the implementation of a new limit (i.e., Proposition 218) and the relaxing of an existing limit (Proposition 39). We have information on 1,462 tax measures and 1,184 bond measures between 1986 and 2000. Forty-six percent of our election data apply to school districts, 27 percent apply to cities, 8 percent apply to counties, and the rest apply to special districts.12 We find that use of tax measures has increased since 1996, not surprisingly given the passage of Proposition 218 and the conclusion of the Proposition 62 court challenges. Because of the changing environment for school districts following passage of Proposition 39 in 2000, we have also included some preliminary information on school bond elections in 2001 and 2002. Before examining specific election results, we next compare patterns in aggregate finances in California to those in the rest of the country. California and U.S. Local Government Finances Thus far, we have discussed the changing constraints placed on local governments and how the state has responded. Part of the aftermath of the Serrano decision and Proposition 13 was a shift in the sources of revenues available. Before examining differences across local governments in California, it is worth looking at whether these changes ____________ 11Cain et al. (1996) found that the use of ballot propositions to fund libraries was very uncommon before 1986. 12Note that limitations on election data mean that we may be missing ballot measures for certain governments. 13 led to differences in the overall level of local government revenues. Has California local finance diverged from that found in the rest of the country? Have spending levels declined? We examine overall local government finance patterns by comparing aggregate local government revenues to revenue levels in the rest of the country. To do this, we use information from the U.S. Bureau of the Census, Census of Governments, for 1972 to 1997.13 We aggregate local revenues to the state level and present figures in real (2000) dollars per capita. California’s local governments spent more on average than most states but less than New York—which is similar to California in terms of wealth, size, and population diversity (Figure 2.1).14 Real local revenues were about $3,000 per person in California in 1972. This level fell following the passage of Proposition 13, but revenue levels fell in New York and the rest of the country as well. Revenues increased after 1982 in California, New York, and the rest of the United States. In Figure 2.2, we compare own-source revenues; that is, we subtract revenues that are raised from state and federally controlled tax sources and then transferred to local governments. In 1972, revenue levels from California’s own sources were similar to those in New York and were much larger than the average in the rest of the country. Following Proposition 13, own-source revenues fell dramatically in California. By 1997, approximately 45 percent of California’s local government funds came from another level of government. Much of this change in state control is due to increased state funds for school districts and counties. We further examine this change in funding by comparing per capita total revenues for California local governments to those in the rest of the country by type of government entity (Table 2.2). Note that although California’s total local revenue levels are higher than those in the rest of the United States, municipal revenues are lower and county and special district revenues are much ____________ 13For more information about Census of Governments data, see Appendix B. 14We have also examined similar figures for other states that may be thought comparable to California, including Texas, Arizona, and Oregon, and find that they have spending patterns similar to the U.S. average. 14 Revenue dollars (2000) 5,500 5,000 4,500 4,000 3,500 3,000 2,500 2,000 1,500 1,000 500 0 1972 1977 New York California United States excluding California 1982 1987 1992 1997 Figure 2.1—Real Per Capita General Revenue, All Local Governments 4,000 3,500 3,000 New York California United States excluding California 2,500 2,000 1,500 1,000 500 0 1972 1977 1982 1987 1992 1997 Figure 2.2—Real Per Capita Own-Source General Revenue, All Local Governments Revenue dollars (2000) 15 Table 2.2 Per Capita Revenue in California and the Rest of the United States Type of Government California All local governments Counties Cities School districts Special districts Excluding school districts 1972 1977 1982 1987 1992 1997 General Revenue 3,119 1,155 635 1,148 182 1,972 3,362 2,922 1,119 927 756 719 1,239 968 248 308 2,123 1,954 3,428 1,099 848 1,079 401 2,349 3,820 1,311 913 1,177 420 2,643 3,820 1,212 944 1,192 472 2,628 United States excluding California All local governments Counties Cities School districts Special districts Excluding school districts 2,068 406 807 757 98 1,311 2,280 2,187 481 478 894 803 779 732 125 173 1,501 1,455 Own-Source General Revenue California All local governments Counties Cities School districts Special districts Excluding school districts 2,226 638 650 705 234 1,521 1,957 1,422 560 378 523 543 680 287 194 214 1,277 1,135 2,554 579 918 845 212 1,709 1,767 478 683 293 314 1,474 2,802 653 972 951 226 1,851 1,966 543 752 352 319 1,614 2,991 713 1,012 1,020 246 1,972 1,908 435 755 419 299 1,489 United States excluding California All local governments Counties Cities School districts Special districts Excluding school districts 1,231 238 527 409 57 822 1,297 1,280 275 296 552 520 388 352 82 112 910 928 SOURCE: U.S. Bureau of the Census (1972–1997) 1,585 393 643 402 147 1,183 1,756 448 689 463 156 1,293 1,853 490 721 473 169 1,380 higher. Throughout this period, California has relied more on special district governments than have other states. California’s local governments are following a different trend from that of the rest of the country in terms of raising local revenues. In the rest of the country, overall own-source revenues increased from 57 percent of funds to 62 percent of funds from 1977 to 1997. In California the trend is reversed, with own-source funds declining from 16 58 percent to 50 percent. These patterns are even more dramatic when examined by specific level of government. County own-source funds declined from about half of funds in 1977 to 36 percent in 1997; in the rest of the United States, those funds increased from 57 percent to almost 70 percent of funds. School districts in both the rest of the country and in California are increasingly under state control, reflecting the wave of school finance equalization cases that have occurred in a majority of states. However, California’s changes are even larger than those found elsewhere. California school districts went from having 55 percent of funds from local sources to having a little over one-third, whereas ownsource revenues in school districts in other states fell only from 54 to 46 percent. Because property tax funds are counted as own-source revenues by the Census of Governments, these changes actually understate the growing reliance of local governments on state sources for finances. Thus, over the past 30 years, school districts and county governments in California have become increasingly reliant on state funds. This has led to a loss of autonomy in fiscal decisionmaking for these levels of governments. California has also become more dependent on special districts to provide local services—with revenues controlled by special districts growing from 7 to 12 percent of local government finances. 17 3. School District Elections and Their Effect on Revenues We saw in Chapter 2 that school districts primarily used the ballot box to gain approval for bond measures to finance school building or modernization programs. Of the 1,168 ballot measures proposed by school districts between 1986 and 2000, 947, or 81 percent, were bond measures. This pattern is very different from other local governments, which depend more on tax measures. This difference in usage is partly due to school districts’ lack of direct control in deciding the level of current fund expenditures in the aftermath of the Serrano lawsuits. In this chapter, we examine how school districts have responded to the lowered voter requirements following the passage of Proposition 39. We then look into what leads school districts to the ballot box and explore differences in capital funding levels across school districts that were and were not successful. Finally, we turn our attention to tax elections and explore the characteristics of school districts that have parcel tax elections and how passage of parcel taxes affects current expenditure levels. School District Bond Elections Over the 1986–2000 period, there were 947 bond elections across the 1,058 school districts. All types of school districts proposed bond measures, with the most activity on a per district basis (approximately 1.3 elections per district) occurring in unified and secondary school districts and very few (0.36 elections per district) occurring in community college districts. Passage rates were highest for elementary school districts and were lowest for community college districts (Table 3.1). The number of school district bond elections increased over time, especially in the later years (Figure 3.1). Before Proposition 39, the largest number of bond elections placed on a single ballot was 48 in November 1997. This activity was partly due to the availability of 19 Table 3.1 Distribution of Bond Measures Proposed and Passed by School Districts, by Type, 1986–2000 Type of District Unified Elementary school High school Community college No. of Districts 325 570 92 71 Average Enrollment 12,706 2,116 5,933 19,732 No. of Measures Proposed 431 363 127 26 Passage Rate (%) 50 62 50 42 Total or average 1,058 6,883 947 54 NOTES: The number of districts and total enrollment are from the California Department of Education, 1999–2000. Community college district enrollment includes part-time enrollment. Number of measures 120 100 80 60 40 20 0 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 NOTES: Each period is one-third of a year. The year labels correspond to the third period, including the November general election. Figure 3.1—Number of Bond Measures Proposed by School Districts, 1986–2002 $3 billion in state matching funds that were approved in the 1996 statewide election with the passage of Proposition 203. The presence of additional state money could have acted as an incentive for local districts 20 Passage rate, % to place bond measures on the ballot, as districts need local funds to be eligible for state funds. Bond measures are also more likely to appear on general election ballots than at other periods during the year. Passage rates increased over time (Figure 3.2). Note that this increase began in the late 1990s, even before the passage of Proposition 39, which lowered the majority required for approval from two-thirds to 55 percent. March 1996 was the election with the highest passage rates (86 percent) before the passage of Proposition 39, but this may be because only seven elections were on the ballot. This passage level was reached and surpassed in the aftermath of Proposition 39, when the lower vote requirement was in place. 100 90 80 70 60 50 40 30 20 10 0 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 NOTE: Each period is one-third of a year. The year labels correspond to the third period, including the November general election. Figure 3.2—Passage Rate of Bond Measures Proposed by School Districts, 1986–2002 Bond Measures Since the Passage of Proposition 39 We next examine in more detail the results of elections that occurred after passage of Proposition 39. In March 2001, eight school districts had elections and five bond measures were passed, but only one school district did not reach the previous threshold of a two-thirds majority. Of 21 the three bond measures that failed, two received more than 55 percent of the vote. Because there were no other general elections occurring in the same jurisdiction, they were ineligible for the lowered vote requirement.1 In November 2001, 32 bond measures were proposed and 29 were approved. This increased passage rate is partly due to the lower threshold for passage. If a two-thirds majority had been in place, six of these bond measures would have failed. In March 2002, the effect of the lower passage requirement was even more dramatic—76 bond measures were proposed and 67 passed, the vast majority of which (42 of the 67 that passed) would have failed if a two-thirds vote had been needed (Table 3.2). There were 103 bond measures on the November 2002 ballot of which 84 passed.2 The other striking result following passage of Proposition 39 was a dramatic increase in local ballot measures by community college districts. Community college districts proposed five bond measures in November 2001 and 14 in March 2002, with four of them passing in November and 12 passing in March. Sixteen bond measures for community college Table 3.2 Number of Bond Measures Proposed and Passed by School Districts Since Passage of Proposition 39 No. of No. of Measures Measures Over TwoProposed Passed Thirds All School Districts March 2001 85 November 2001 32 29 March 2002 76 67 November 2002 103 84 Community College Districts 4 23 25 41 March 2001 November 2001 March 2002 November 2002 0 00 5 43 14 12 3 16 15 4 ____________ 1The lower requirement is applicable only if another election is already scheduled. 2Information on the November 2002 ballot is preliminary and we would like to thank Deborah Finestone of the Bond Buyer and Patti Herrera of the Coalition for Adequate School Housing for providing us with a list of these measures. 22 district funding were on the November 2002 ballot. Before 2001, community college districts had proposed only 26 bonds of which 11 had passed. Regional Patterns in Bond Elections We next examine differences in proposal and passage rates across regions in the state.3 The Central Valley area and the southern region of the state proposed more bond measures than the other regions (Table 3.3). However, the San Francisco Bay Area, with 163 school districts and 197 bond elections, had the highest average number of measures Table 3.3 Number of Bond Measures Proposed and Passed, by Region, 1986–2002 Region Northern Bay Area Valley Coastal Southern No. of Districts 240 163 262 99 223 1986–2000 No. of Measures Passage Proposed Rate (%) 124 38 197 75 242 45 93 55 265 57 2001–2002 No. of Measures Passage Proposed Rate (%) 24 75 42 93 48 83 16 81 54 81 Total or average 987 921 55 184 84 NOTE: The following counties are contained in each regional grouping: Northern—Alpine, Amador, Butte, Colusa, Del Norte, El Dorado, Glenn, Humboldt, Lake, Lassen, Mendocino, Modoc, Nevada, Placer, Plumas, Shasta, Sierra, Siskiyou, Sutter, Tehama, Trinity, and Yuba; Bay Area—Alameda, Contra Costa, Marin, Napa, San Francisco, San Mateo, Santa Clara, Solano, and Sonoma; Valley—Calaveras, Fresno, Inyo, Kern, Kings, Madera, Mariposa, Merced, Mono, Sacramento, San Joaquin, Stanislaus, Tulare, Tuolumne, and Yolo; Coastal—Monterey, San Benito, San Luis Obispo, Santa Barbara, Santa Cruz, and Ventura; Southern— Imperial, Los Angeles, Orange, Riverside, San Bernardino, and San Diego. ____________ 3For the remainder of the analysis, we exclude community college districts from our analyses. This is partly due to the small number of ballot measures these districts used and also to the different population they served. 23 proposed—1.2 bond measures per district. The Bay Area also had the highest passage rate—75 percent before 2001 and 93 percent after the passage of Proposition 39. School districts in the northern region had the lowest bond proposal and passage rate, with 240 districts proposing only 124 bond measures, of which only 38 percent passed. After Proposition 39, passage rates increased in all regions, most notably in the northern region and the Central Valley. The patterns we find across regions resemble those within regions if we look at the prevalence of proposing elections in different counties. We find that most elections occurred in Los Angeles County (98), San Diego County (52), and other Southern California counties (Figure 3.3). This partly reflects the higher number of school districts found in 0 1–9 10–24 25–44 45–98 Figure 3.3—Number of Bond Measures Proposed by School Districts, 1986–2000 24 counties in Southern California.4 A large number of elections also occurred in Santa Clara County (45) and many other Bay Area counties. Passage rates were high in most Bay Area counties (see Figure 3.4). Mono, Plumas, and San Francisco Counties had a 100 percent passage rate, although they had very few elections because of having only one or two school districts per county. Los Angeles County had the most bond elections (18) followed by San Diego, Sacramento, and Santa Clara. The eight elections placed on the ballot in Orange County over the last two years constituted more than half the number placed on the ballot over the prior 14 years. No bond measures 0–25 26–50 51–75 76–100 Figure 3.4—Passage Rate of Bond Measures Proposed by School Districts, 1986–2000 ____________ 4The number of school districts in each county, the number of bond elections, and passage rates can be found in Appendix Table C.1. The maps exclude elections held by community college districts. 25 Passage rates also increased dramatically in virtually all the counties that had an election (see Appendix Table C.1). Distribution of Bond Measures Across School Districts Up to this point, we have examined patterns in bond elections in California, but we have not differentiated between instances where a given school district had multiple elections or many school districts each had a single election. We now turn our attention to the frequency of elections across school districts between 1986 and 2000. Of the 987 non–community college districts, about half (546) held at least one election. Of these, 58 percent of school districts held one election, 24 percent held two, 11 percent held three, and only 6 percent held four or more elections (Table 3.4). We observe a decline in passage rates as the number of elections increases. Thus, school districts appear to return to the ballot box if they were originally unsuccessful in gaining voter permission to issue a bond measure. For school districts that went to the ballot box up to four times, the amount raised was fairly constant and averaged between $5,000 and $7,000 per pupil. Thus, it seems that school districts that wanted to raise a certain amount of money returned to the ballot box until it was raised. If in this earlier period the passage rate for school construction measures had been 55 percent (the required supermajority under Table 3.4 Distribution of Bond Measures Proposed by School Districts, 1986–2000 No. of Measures Proposed 0 1 2 3 4 5 6+ Total or average No. of Districts 441 319 131 62 22 8 4 987 Passage Rate (%) 81 52 34 34 25 19 66 Average $ per Student Proposed Passed 00 7,166 5,317 13,525 6,562 16,541 5,130 17,249 4,906 53,126 14,393 25,394 4,908 10,977 5,708 26 Proposition 39) rather than two-thirds, 89 percent of bond measures would have passed. However, if the vote requirement had been lower, there would have been a different makeup of elections, as school districts that were successful on their first ballot would not necessarily have returned to the ballot box. Therefore, the amount of money raised would have probably increased although not by the amount of all bond measures proposed. Of the 169 non–community college school districts that have proposed a bond measure since the passage of Proposition 39, 46 did not propose a bond measure in the 1986–2000 period, 52 proposed at least one bond measure before but never successfully passed a bond, and 71 districts were able to pass a bond measure under the two-thirds requirement. Thus, it seems that lowering the vote requirement increased the successful usage of the ballot box by school districts. About 22 percent of the 546 school districts that had proposed at least one bond measure were ultimately unsuccessful as of 2000 (Table 3.5). Thirty-six percent of school districts (or 358) had one successful bond measure, 62 school districts had two, six had three measures pass, and only one school district (San Francisco Unified School District) passed four bond measures. On average, school districts that passed two or three bond measures had a higher amount of bond funds per student. Surprisingly, San Francisco Unified School District, which passed four Table 3.5 Distribution of Bond Measures Passed by School Districts, 1986–2000 No. of Measures Passed 0 1 2 3 4+ Total or average No. of Districts 560 358 62 6 1 Passage Rate (%) 84 84 85 100 Average $ per Student Proposed Passed 2,300 0 9,986 6,613 15,909 10,960 13,956 10,714 6,286 6,286 987 66 10,977 5,708 27 measures, raised slightly less than $6,300—less than the average amount raised by school districts that passed only one measure. Determinants of School District Bond Elections and Capital Expenditures We turn now to the question of which characteristics seem to lead school districts to the ballot box. Do these characteristics reflect differences among districts facing growing and shrinking enrollments? Do they reflect differences in the income levels or property values across districts? And how does the use of the ballot box influence overall levels of capital financing? We limit our sample to districts that can be linked to demographic data, and we analyze unified school districts separately because they serve the vast majority of California’s students and are much larger. Of the 726 school districts for which we have demographic information as of 2000, 295 never proposed a bond measure, 78 proposed but never passed a bond measure, and 353—almost half of all school districts—passed a bond measure. Thus, the percentage of school districts that were successful in passing new bond measures is slightly higher in the sample of schools remaining. This result is not surprising, as the omitted school districts are mainly in rural areas that are not facing enrollment growth.5 We first examine factors that may have led to differences in school districts proposing or passing new measures. That is, we examine demographic differences among school districts that did not propose a ballot measure, those that proposed but did not pass at least one measure, and those that were successful in passing at least one new bond measure. We would expect districts with growing student populations to require more facilities financing, so we examine the effect of student enrollment sizes and enrollment growth on the decision to attempt to pass a bond measure. Because limits on school district debt are based on assessed ____________ 5Information on school district demographics is from the U.S. Department of Education (1990) based on 1990 Census information. Unfortunately, this information is not available for school districts in Butte, El Dorado, Humboldt, Madera, Monterey, Napa, Santa Barbara, or Siskiyou Counties. We also combine information on districts that merged over this period. We are left with 726 districts for the remainder of our analysis. 28 value (1.25 percent of assessed value for elementary or secondary districts and 2.5 percent for unified districts), there is a direct relationship between assessed value and the maximum amount of money that can be raised. We would also expect school districts with a higher percentage of older voters to be less likely to pass new school bonds, as they would not directly benefit from the new or improved facilities.6 We also examine how differences in family income, the racial makeup of the population, and the percentage of homeowners in a district affect the prospects of proposing or passing a bond measure. We find that larger school districts were more likely to have a bond election and that, on average, those that were successful were very large. School districts that did not have any bond elections had student populations of about 2,300 in 1999–2000, those that had a bond election but were unsuccessful had an average of 6,900 students, and successful school districts had about 10,200 students. Thus, higher enrollment increases the probability of having a bond election. See Table 3.6 for the average level of enrollment and the other descriptive characteristics of these three sets of school districts. School districts that were successful at passing a bond measure had higher enrollment growth than both districts that never proposed an election and those that failed to ever pass a bond measure. School districts that were never successful in passing a bond measure had lower assessed values, whereas successful school districts had lower assessed value per student than districts that never proposed a bond measure but had higher assessed value than those that failed to pass a bond measure. Thus, assessed value seems to affect school districts’ ability to pass a bond measure. Average household income also differs across the three sets of districts. Income was highest for districts that successfully passed a bond measure and lowest for districts that proposed but did not pass a bond. School districts that held bond elections (whether successful or not) had a higher ____________ 6These households may benefit by improved school facilities indirectly if these improvements lead to higher home prices. For a discussion of house price capitalization and school quality, see Sonstelie, Brunner, and Ardon (2000). 29 Table 3.6 Demographic Characteristics of School Districts, by Bond Measure Experience Did Not Proposed and Proposed Overall Propose Did Not Pass and Passed All School Districts Average daily attendance 6,653 2,339 6,909 10,202 % growth in average daily attendance, 125.2 119.6 126.0 129.7 1989–1998 Assessed value per student, $ 654,424 746,373 504,179 610,782 Mean household income, $ 44,661 42,423 37,705 48,068 % over age 65 11.3 12.0 11.5 10.7 % nonwhite 36.8 32.5 39.3 40.0 % homeowner 64.0 64.9 67.0 62.6 No. of districts 726 295 78 353 Unified School Districts Average daily attendance 13,478 5,812 8,422 17,716 % growth in average daily attendance, 125.4 116.6 125.8 128.5 1989–1998 Assessed value per student, $ 416,481 517,473 257,085 425,880 Mean household income, $ 44,429 38,722 37,219 48,578 % over age 65 11.3 12.8 11.9 10.6 % nonwhite 39.3 34.6 44.1 39.6 % homeowner 63.0 62.9 66.1 62.1 No. of districts 246 54 43 149 percentage of nonwhite students in the district. All other demographic characteristics were similar across the three groups of districts. The overall numbers may mask differences in behavior among unified school districts and elementary and high school districts. Thus, we now turn our attention to unified school districts in California. Of the 246 unified districts in our sample, 54 never proposed a school bond measure, 43 proposed at least one measure but never passed one, and 149 passed at least one measure. We find that average attendance levels were larger in unified districts for all three groupings. Unified school districts that had bond elections tended to be larger, and those that were successful at passing new measures were larger still than those districts that did not propose or were not successful in passing a bond measure. Successful districts also had higher family incomes than districts that did 30 not propose or pass any bond measures. Districts that proposed bond measures were faster-growing and had a higher average percentage of nonwhite student enrollment than those that did not propose a bond measure. Unified school districts that were successful had higher assessed value than those that were unsuccessful but lower assessed value than those that never proposed a measure. Demographic characteristics of unified school districts can be found in the lower panel of Table 3.6. Does holding an election affect overall capital revenues? School districts that did not hold a successful bond election may have been able to raise funds using developer fees or state aid. Thus, we now turn our attention to how much money was raised by each group of school districts for capital expenditures. If we compare capital revenues per student spent in the 1992–2000 period, we find that school districts that passed a bond measure between 1986 and 2000 had higher bond revenues and also had substantively higher total per pupil capital revenues. Figure 3.5 shows average per pupil bond revenues and overall capital revenues by election success. School districts without a successful bond election spent about $3,000 per student on capital projects, whereas school districts that were successful spent more than double that amount, $6,600. Not surprisingly, very little funding came from bond money in school districts that did not have at least one successful ballot measure. The small amount of bond funding listed for districts without an election was from the 1 percent of these districts that had a bond election prior to our sample period. School districts that were unsuccessful at passing a local bond did receive a higher amount of state aid on average (Table 3.7). Other local sources included revenue from Developer Fees and Certificates of Participation (COPs).7 School districts that had successful bond elections also were successful in raising other local funds and had higher levels of revenues from fees and COPs. It may be that the underlying characteristics that lead voters to pass new bond measures (such as increased enrollment growth) will also lead to support for other local funds. ____________ 7See Brunner and Rueben (2001) for a discussion of overall school facility funds. 31 Revenue dollars (2000) 7,000 6,000 5,000 4,000 Average district Did not propose Proposed and did not pass Proposed and passed 3,000 2,000 1,000 0 Capital revenue Bond revenue Figure 3.5—Average Total Capital Revenue and Bond Revenue per Student, 1992–2000 Table 3.7 School District Per Pupil Capital Revenue, by Bond Measure Experience Did Not Overall Propose All School Districts Total capital revenues per student Bond revenues per student State funds per student Fees per student COPs per student 4,705 1,803 1,273 640 132 2,852 116 1,304 493 64 Unified School Districts Total capital revenues per student Bond revenues per student State funds per student Fees per student COPs per student 4,397 1,780 1,087 575 171 2,621 186 842 373 169 NOTE: Amounts are in constant year 2000 dollars. Proposed and Proposed Did Not Pass and Passed 3,072 0 1,532 608 161 6,615 3,607 1,190 769 182 2,691 0 1,542 506 116 5,534 2,865 1,045 669 187 For unified districts, average funding levels for each group were slightly lower than the average for all school districts. However, as with average numbers for all districts, funding levels for unified districts that 32 held successful bond elections were, on average, twice as high as for those that did not, and the largest increase in spending came from bond funds (Table 3.7, bottom panel). The results presented thus far show average differences in the three groups of school districts but do not make clear which differences are important in the proposal or passage process and how passing a bond measure affects total capital spending. To examine how these different characteristics interact and cumulatively influence the decision to propose bond measures and the probability that voters will pass them, we use regression analysis. Regression analysis allows us to disentangle relationships among variables and to estimate how much of the difference seen across regions is actually driven by differences in assessed values and enrollment growth. Using these estimates allows us to predict how proposal rates would differ if we were to change only one characteristic of a school district.8 We first examine which factors influence the decision to propose a bond measure. (These results for all school districts and unified districts only can be found in the first two columns of Appendix Table C.2.) We find that after controlling for demographic characteristics, the probability of proposing a bond measure for an average district is 52 percent. In Table 3.8, we provide information on the influence of different school district characteristics by estimating the change in probabilities of proposing and passing a bond measure as district characteristics change.9 We find that elementary school districts are less likely to propose a bond measure than are either unified or high school districts (41 percent for elementary school districts, 66 percent for unified districts, and 64 percent for high school districts). We also find that larger enrollments ____________ 8We follow a similar estimation strategy to that used by Brokaw, Gale, and Merz (2001) in modeling voter elections. For a more complex modeling strategy, see Balsdon, Brunner, and Rueben (2002), who use a three-equation model to examine the decision to propose a bond measure, passage rates, and the amount passed, controlling for sample selection for unified districts. 9For our estimates, we calculate passage rates for an “average” school district that has characteristics equivalent to those of the median school district and compare the effect of changing a district characteristic to that found at the 25th or 75th percentile. The values of these exercises can be found in Appendix Table C.3. 33 Table 3.8 Estimated Change in Probability of Proposing and Passing Bond Measures Average district Unified district Elementary school district High school district Average daily attendance Average daily attendance growth, 1989–1998 Assessed value per student Mean household income Percentage homeowners Probability of Proposing 52.3 66.4 41.2 64.4 Low High 49.4 60.2 51.2 53.4 Probability of Passing 42.3 48.9 36.3 54.2 Low High 40.5 47.4 41.2 43.4 Probability of Passing If Proposed 81.1 71.9 85.7 80.9 Low High 81.1 81.2 80.2 82.0 52.5 51.9 51.5 53.3 50.8 53.8 42.8 41.3 81.4 80.5 39.9 45.5 72.0 89.8 44.7 39.9 88.7 70.7 NOTES: Low and high probabilities correspond to the 25th and 75th percentiles, respectively. An average district corresponds to a district with median characteristics. See Appendix Table C.3 for the corresponding values of the variables. increase the probability of proposing a bond measure. For a district with average enrollment, or 2,211 students, the probability of proposing a bond measure is 52 percent, whereas for a district with a high enrollment, or 7,039 students, the estimated probability of proposing a bond measure would increase by 8 percentage points to 60 percent. Enrollment growth also has a statistically significant and positive effect on the probability of proposing or passing a bond measure, although the changes in probability are small. Our results are weaker when we examine only unified school districts but they follow the same patterns. We next examine the probability of passing a bond measure across school districts. We find that elementary school districts are again least likely to pass new bonds (36 percent), whereas high school districts, which have nearly the same estimated probability of proposing a measure as unified districts, have a higher probability of passing a bond measure overall (54 versus 49 percent). Higher enrollments also increase the probability of passing bond measures, as does higher household income. Moving from the median average daily attendance to a school with 34 relatively high enrollment increases the probability of passing a measure from 42 to 47 percent. Changing the average household income in a district from the state average ($40,754) to a lower level ($32,712) also diminishes the chances of passing a measure, from 42 to 40 percent. School districts with a higher percentage of homeowners are less likely to pass a new bond measure—possibly because they directly bear the burden of paying back the bond. If the percentage of homeowners in a district changes from 73 percent to 57 percent, the probability of passing a measure increases 5 percentage points (from 40 to 45 percent). If we limit our regressions to unified school districts, we find similar results. Although elementary school districts are less likely than unified and high school districts to propose bond measures, their measures are more likely to pass once on the ballot. If an elementary school district places at least one measure on a ballot, its estimated chance of passing a bond is 86 percent, whereas a unified district’s average passage rate conditional on proposing is 72 percent and a high school district passage rate is 81 percent. The lower passage rate for unified districts (as compared to elementary and high school districts) may have to do with the larger size and increased number of schools in the district. Finally, we use regression analysis to explore how spending varies across each group of school districts by examining demand for capital expenditures. These results are found in Appendix Table C.4. We follow the methodology used in Bergstrom, Rubinfeld, and Shapiro (1982) and Borcherding and Deacon (1972). We focus on spending levels in the period between 1992 and 2000, and we collapse spending at any point in that period into one aggregate figure.10 State matching funds are primarily based on enrollment growth; thus, we would expect to see a positive relationship between spending and enrollment numbers and growth rates. This is indeed the case. A district with an average daily attendance of 2,211 has estimated total capital revenues of $2,004 per student, whereas a district with larger enrollment (7,039) has estimated revenues of $2,538 per student. We also find a positive relationship between spending levels and assessed value per student. The ____________ 10For a more technical discussion of school bond elections in unified districts that includes variation over time see Balsdon, Brunner, and Rueben (2002). 35 assessed value per student varies greatly across districts; an average district’s value is about $400,000, whereas a low assessed value district has a value of about $255,000. Lowering the assessed value from $400,000 to $255,000 would lead to a 15 percent decline in capital spending per student, from $2,004 to $1,711. Economic theory predicts that districts with higher assessed value are able to raise more funds because a given increase in property tax rates will raise more money in a district with a higher level of assessed value than in a district with less property wealth. Other household demographics do not significantly affect spending levels, although high school districts receive lower funds on a per pupil basis ($1,415) than do elementary ($2,206) or unified ($1,904) school districts. Appendix Table C.4 also presents results for unified school districts only, and we find very similar patterns to the sample as a whole. After controlling for other district characteristics, we still find regional differences in capital revenues. Bay Area districts raise $3,500 on average compared to $2,472 for coastal districts and about $2,000 per pupil for districts in other regions. School District Parcel Tax Elections Tax elections make up about 20 percent of all school district measures. The only tax measures proposed by school districts are parcel taxes. The small reliance on tax measures is partly due to revenue limits placed on school districts and the relatively small amount of money per pupil raised by a parcel tax.11 Table 3.9 presents information on tax measure elections for the different types of school districts. Elementary school districts are the most likely to propose a parcel tax and have the highest passage rate. Only one community college district (Los Angeles Community College District) proposed a parcel tax during this period. Parcel taxes differ from property taxes in that they are not based on the assessed value of property but rather on a set amount of money per structure—sometimes differing by type of structure (residential, ____________ 11See Sonstelie and Richardson (2001, Chapter 9), for more information on the role that parcel taxes play in current school district finances. 36 Table 3.9 Distribution of Parcel Tax Measures Proposed and Passed by School Districts, by Type, 1986–2000 Type of District Unified Elementary school High school Community college No. of Districts 325 570 92 71 Total Enrollment 12,706 2,116 5,933 19732 No. of Measures Proposed 86 117 18 1 Passage Rate (%) 44 63 56 0 Total or average 1,058 6,883 222 55 NOTES: Number of districts and total enrollment are from the California Department of Eduction, 1999–2000. Community college district enrollment includes part-time enrollment. commercial, or multiunit).12 School districts typically proposed taxes between $20 and $200 per parcel. School district parcel taxes were usually imposed with specific time periods for collections, usually around 4–5 years, although a few were proposed for 10 or more years, and two were proposed without expiration dates. Berkeley Unified School District proposed parcel taxes over this period that specified an amount of money per square foot of space. It was also the only district in our sample to propose parcel taxes with different amounts of money collected from residential and commercial space. Thus, the majority of school districts that proposed parcel taxes proposed a set amount per structure for a given number of years. In the next chapter, we examine city parcel tax measures and find a more varied pattern of usage. Far fewer tax measures were proposed than bond measures, averaging a little less than 20 measures per year. The number of measures proposed peaked in 1991, when 33 measures were proposed, but that number has dropped more recently (Figure 3.6). The state was facing budget difficulties in the early 1990s and was not increasing funding for school districts. Passage rates increased throughout this period, but this may reflect the decline in the number of ballot measures proposed (Figure 3.7). ____________ 12In contrast, if a bond measure is passed it leads to a temporary increase in property tax rates. 37 Number of measures 40 35 30 25 20 15 10 5 0 1986 1988 1990 1992 1994 1996 1998 2000 2002 Figure 3.6—Number of Parcel Tax Measures Proposed by School Districts, 1986–2002 100 90 80 70 60 50 40 30 20 10 0 1986 1988 1990 1992 1994 1996 1998 2000 2002 Figure 3.7—Passage Rate of Parcel Tax Measures Proposed by School Districts, 1986–2002 Passage rate, % 38 Regional Patterns in Parcel Tax Elections The vast majority of parcel taxes, 68 percent, were proposed in the Bay Area, where passage rates were also the highest (Table 3.10). As with bond measures, the northern region proposed the fewest measures per district. Passage rates were lower than those of bonds in all regions, with the coastal region having the lowest passage rate, 8 percent. If we look across counties, we again see that Bay Area counties, especially Marin County with 48 measures, proposed the most parcel taxes (Figure 3.8).13 School districts in Sonoma, Santa Clara, and Los Angeles Counties placed 24 measures each during this time period, although the Los Angeles figure partly reflects the higher number of school districts in the county. In 32 counties, no school districts proposed a parcel tax. Yolo County passed all four measures that were proposed, although these results are due to elections held only in the Davis School District. Marin, with the highest number of measures proposed, had the second-highest passage rate, 85 percent, passing 41 of the 48 measures proposed. Table 3.10 Distribution of Parcel Tax Measures Proposed and Passed by School Districts, by Region, 1986–2000 Region Northern Bay Area Valley Coastal Southern No. of Districts 240 163 262 99 223 No. of Measures Proposed 9 151 17 13 31 Passage Rate (%) 44 68 41 8 26 Total or average 987 221 55 ____________ 13Appendix Table C.5 includes county-level statistics for Figure 3.8. 39 0 1–4 5–9 10–19 20–48 Figure 3.8—Number of Parcel Tax Measures, by School District, 1986–2000 Distribution of Tax Measures Across School Districts Unlike bond measures, parcel taxes were proposed by a relatively small group of districts, with 88 percent of districts never proposing any tax measures. About half the school districts that proposed tax measures proposed only a single one; one-quarter proposed two measures, and one-quarter proposed three or more measures (Table 3.11). Only 55 school districts successfully passed a parcel tax. Passage rates increased as the number of measures proposed increased—so proposing and voting behavior seem very different from that found for bond measures. For bond measures, the majority of districts that had elections had a single successful election, but for parcel tax measures, districts that had elections often passed multiple measures over the 1986– 40 Table 3.11 Distribution of Parcel Tax Measures Proposed by School Districts, 1986–2000 No. of Measures Proposed 0 1 2 3 4 5 Total or average No. of Districts 871 57 29 16 12 2 Passage Rate (%) 25 36 79 85 80 987 42 2000 period. This pattern usually occurred because districts would propose a new parcel tax to replace an expiring tax (Table 3.12). By 2000, only five districts had two concurrent parcel taxes in place at the same time, although for most, the total amount accumulated was still less than $200. The only districts with parcel taxes higher than $200 per parcel in 2000 were Kentfield ($295), Lagunitas (two parcel taxes raising $145 and $165), Loma Prieta (two $150 parcel taxes), Los Gatos ($250), Mill Valley ($275), Piedmont ($497 and $130 parcel taxes), and Ross ($495). Table 3.12 Distribution of Parcel Tax Measures Passed by School Districts, 1986–2000 No. of Measures Passed 0 1 2 3 4+ Total or average No. of Districts 932 18 14 17 6 987 Passage Rate (%) 88 88 87 100 42 41 Determinants of School District Tax Elections and Current Revenues In the previous section, we saw that relatively few school districts propose parcel taxes and that few funds are raised this way. We now examine whether these school districts look different from school districts that never proposed a parcel tax and those that proposed but never passed a parcel tax.14 As was the case for bond measures, we have demographic information on only a limited set of school districts, 726. Of these districts, 617, or 85 percent, never proposed a tax measure, 54 proposed but did not pass a tax measure, and 55 passed at least one tax measure. Table 3.13 presents information on the demographic characteristics of all school districts and unified school districts by parcel tax usage. School districts that passed a tax measure were smaller than other districts. Student populations of school districts with parcel tax measures were on average about 3,800 as compared to 6,800 students on average in districts that did not propose elections and 7,900 students in districts that were unsuccessful. Assessed value is much higher on a per pupil basis in those districts that passed at least one tax measure, which partly reflects the smaller student populations in these districts. Mean household income was also much higher for districts that passed a parcel tax. They also had fewer nonwhite students than did districts that did not propose parcel tax measures. We find similar patterns if we restrict our sample to unified school districts, although in this limited sample it is striking how similar unified school districts that proposed and did not pass tax measures are to those that were successful at passing ballot measures. That is, for unified districts, only districts with high property values and high income seem to propose tax measures. ____________ 14We have also examined the differences across school districts that have and have not proposed a parcel tax using a regression framework. We find differences across types of districts, but our results lack statistical significance because of the limited number of school districts that have passed parcel taxes. We find that elections are more prevalent in the Bay Area and school districts with higher-income households and fewer nonwhite households are both more likely to propose and pass a parcel tax. These regressions are available from the authors upon request. 42 Table 3.13 Demographic Characteristics of School Districts, by Parcel Tax Experience, 1986–2000 Characteristic Did Not Proposed and Proposed Overall Propose Did Not Pass and Passed All School Districts Average daily attendance 6,653 % growth in average daily attendance, 125.2 1989–1998 Assessed value per student, $ 654,424 Mean household income, $ 44,661 % over age 65 11.3 % nonwhite 36.8 % homeowner 64.0 No. of districts 726 6,796 126.1 614,467 41,318 11.1 39.2 63.6 617 7,918 119.9 3,802 121.0 729,596 1,028,874 56,172 70,859 11.5 13.4 29.5 17.4 63.8 68.3 54 55 Unified School Districts Average daily attendance 13,478 % growth in average daily attendance, 123.8 1989–1998 Assessed value per student, $ 416,481 Mean household income, $ 44,429 % over age 65 11.3 % nonwhite 39.3 % homeowner 63.0 No. of districts 246 14,210 124.8 389,930 41,523 11.3 42.5 63.2 204 11,116 119.0 7,773 120.0 580,401 60,091 11.5 23.5 62.7 27 482,520 55,766 11.6 25.1 60.8 15 If we specifically examine regional patterns in proposing or passing tax measures, we find that school districts in the Bay Area are much more likely to propose and pass at least one tax measure. Forty-seven percent of Bay Area school districts proposed a parcel tax and 30 percent successfully passed at least one. School districts in other regions of the state had much lower proposal and passage rates. Less than 3 percent of districts in other regions passed any parcel taxes. Parcel tax revenues are concentrated in the San Francisco Bay Area in high-income and high-assessed-value districts. Although not related directly to property values, this difference may lead to inequities in current spending levels related to property wealth—the inequities found to be unconstitutional in the Serrano v. Priest decision. Therefore, we examine current revenues across school districts. Overall, school districts 43 that had a successful parcel tax in place raised $600 more per pupil than school districts that never proposed a parcel tax and $700 more than school districts that were unsuccessful (Table 3.14). These differences are only partly explained by parcel tax revenues, which averaged $375 per pupil for school districts with a successful election. There are also differences in other local taxes and some categorical programs.15 Thus, school districts that passed local parcel taxes were more successful at raising other local funds as well. Similar patterns exist for unified districts, where districts with parcel taxes in place raised $400 more per student. Table 3.14 Fiscal Characteristics of School Districts, by Parcel Tax Experience, 1986–2000 Did Not Proposed and Proposed Overall Propose Did Not Pass and Passed All School Districts Total current revenues per student Non–ad valorem taxes Parcel taxes 6,420 37 28 6,384 3 0 6,263 11 0 6,980 451 375 Unified School Districts Total current revenues per student Non–ad valorem taxes Parcel taxes 6,418 25 19 6,402 5 0 6,318 17 0 6,816 307 301 NOTE: Amounts are in constant year 2000 dollars. Summary In this chapter, we have examined how school districts use bond and tax measures and the effects of these measures on school district finances. We find that school districts relied more on bond measures than tax measures, possibly reflecting limitations on current expenditures because of school finance equalization rulings. About half of all districts ____________ 15The non–ad valorem category of revenues includes parcel taxes and other local revenue sources not subject to revenue limits. These taxes include sales taxes, maintenance assessment district funds, community redevelopment funds not subject to revenue limits, and penalties and interest from delinquent taxes not subject to revenue limits. 44 successfully passed a bond measure; of these districts, most passed only one measure. School districts in the Bay Area were the most successful historically in gaining voter approval for new bonds. School bond elections increased after the passage of Proposition 39 and passage rates dramatically increased throughout the state. The preliminary evidence suggests that the lower vote threshold increased the set of school districts proposing new measures—most notably expanding the ability of community college districts to raise funds locally. Of 67 new school bonds that were approved in March 2002, two-thirds (42) would not have passed at the old supermajority level. In examining school facility revenues, we find that school bond funds were an important component of capital expenditures—making up approximately 40 percent of capital revenue funds and about half of all local funds. The probability of proposing or passing a bond measure depends on enrollment size, enrollment growth, and average household income. The amount of money approved depends on enrollment, enrollment growth, and the assessed value of property in the school district. Districts that had higher assessed value raised more funds. This pattern in part reflects current debt limits, which are based directly on assessed value, and it has led to unequal capital spending across school districts with different levels of assessed value. School districts in the Bay Area were also more likely to propose and pass bond measures and also to have higher levels of capital spending. Finally, we find that parcel taxes were used by relatively few school districts but that school districts that were successful at passing a parcel tax generally re-approved the tax over time. Parcel taxes were most often proposed by Bay Area school districts and were used by smaller school districts that contain wealthier households. This may raise equity concerns because this pattern leads to different levels of current spending across districts with different property wealth. However, the amount of money raised per pupil was relatively small. School districts that proposed but were unsuccessful in passing a parcel tax had lower average spending than districts that did not propose a parcel tax; those that were successful in passing a tax spent $600 more per pupil per year. 45 4. City Fiscal Measure Elections and Their Effect on Revenues Cities are the level of government, after school districts, that propose the most fiscal measures. Cities had the smallest increase in state revenues following Proposition 13 and are most reliant on their own revenue sources. Cities also have access to a fairly wide array of local revenues including parcel taxes, sales taxes, and various business taxes.1 New revenue sources can also be used to fund a myriad of different services including police, fire, library services, trash collection, and general government services. As of 1997, there were 471 incorporated cities in California. From 1986 to 2000, 728 measures were placed on the ballot by 267 cities. The vast majority of measures were to raise taxes (586 out of 728). We will begin by briefly investigating bond elections, comparing the uses of these funds to those passed by school districts, and the demographic characteristics of cities that have and have not proposed bond measures. We will also examine how these measures have affected capital revenue sources. The main analysis of this chapter, however, will explore the characteristics of tax measures and how spending levels vary across cities that have or have not successfully passed new taxes using the ballot box. We will also discuss the prevalence of new tax and fee measures in the aftermath of Proposition 218, the 1996 statewide initiative that confirmed the requirement for voter approval for general taxes and expanded the requirements of voter approval to certain fees and assessments. Finally, we investigate the demographic characteristics that lead to use of the ballot box and compare how sources of revenues have ____________ 1This chapter expands on prior work done by researchers at PPIC on city governments and their reliance on different sources of revenue. Lewis and Barbour (1999) examined the role of the local sales tax on city government structure and Dardia (1998) explored the role of redevelopment zones in reallocating funds between county and city governments. 47 varied over time in cities that have and have not passed fiscal measures. Unfortunately, we are potentially missing some information on fiscal elections that occurred in off-cycle or odd-year elections in the early 1990s. We find that in the period for which we have complete ballot information, local measures were less likely to be proposed in off-cycle elections; in cities with on-cycle versus off-cycle mayoral elections, we find no difference in the probability of never having a tax measure or of never successfully passing one.2 Municipal Bond Elections Municipal bonds were usually used to fund capital projects or to purchase land or equipment—parkland purchases, fire and police construction projects or equipment purchases, and library construction. A cluster of seismic safety projects in the early 1990s followed the Loma Prieta earthquake, which we classified under general government or by the service provided by the building to be refurbished (Table 4.1). Passage rates varied substantially across types of bond measures—with much higher passage rates for hospital (80 percent) and flood control (75 Table 4.1 Number of Bond Measures Proposed and Passed, by Function, 1986–2000 Function General government Fire, police, jails Hospital and emergency services Recreation and parks Library Transportation Flood control Buildings Other No. of Measures Proposed 9 24 5 40 19 14 12 9 10 Passage Rate (%) 44 42 80 33 58 43 75 56 70 Total or average 142 49 ____________ 2We use the classification of cities into those that have on-cycle or off-cycle elections found in Hajnal, Lewis, and Louch (2002). 48 percent) measures than for other bond requests. Funding to buy parkland or to refurbish playgrounds was proposed most often and faced the lowest passage rate, passing only one-third of the time. This partly reflects a city re-proposing a bond measure after it failed on an earlier ballot, a pattern similar to what we found for school districts. The number of bond measures proposed by cities reached the highest point in 1990 with 22, following the Loma Prieta earthquake, then declined in the mid-1990s and increased again in 2000 (Figure 4.1). Passage rates have also gone up since 1986, although this increase in passage rates partly reflects the smaller number of measures placed on the ballot (Figure 4.2). This increase in approval rating beginning in 1998 is similar to results for school districts, where bond passage rates increased even before the passage of Proposition 39. Thus, it seems there was increased support on the part of voters for infrastructure projects even beyond school facilities. As Table 4.2 shows, bonds passed 45 percent of the time before 1996, 30 percent of the time in 1996–1997, and 76 percent of the time in the past few years. 40 35 30 25 20 15 10 5 0 1986 1987 1988 1989 1990 1991 1992 1994 1996 1997 1998 1999 2000 NOTE: 1993 and 1995 are omitted because of a lack of information about fiscal measures. Figure 4.1—Number of Bond Measures Proposed by Municipal Governments, 1986–2000 49 Number of measures Passage rate, % 100 90 80 70 60 50 40 30 20 10 0 1986 1987 1988 1989 1990 1991 1992 1994 1996 1997 1998 1999 2000 NOTE: 1993 and 1995 are omitted because of a lack of information about fiscal measures. Figure 4.2—Passage Rate of Bond Measures Proposed by Municipal Governments, 1986–2000 Table 4.2 Number of Bond Measures Proposed and Passed, by Timing, 1986–2000 Before 1996 In 1996–1997 After 1997 No. of Measures Proposed 111 10 21 Passage Rate (%) 45 30 76 No. of Measures per Year 14 5 7 Total or average 142 49 11 Regional Patterns in Bond Elections The Bay Area and the southern region have proposed more bond measures than other regions in the state (Table 4.3). This pattern is not surprising; of the 471 incorporated cities in the state in 1997, 100 (21 percent) are in the Bay Area and 192 (41 percent) are in the southern region. Passage rates vary, with the Bay Area having the highest rate at 62 percent, and the valley region having the lowest at 13 percent. In the northern region of the state, the 62 cities proposed only four bond 50 Table 4.3 Number of Bond Measures Proposed and Passed, by Region, 1986–2000 Region Northern Bay Area Valley Coastal Southern Total or average No. of Cities 62 100 75 42 192 471 No. of Measures Proposed 4 60 8 12 58 142 Passage Rate (%) 50 62 13 50 40 49 measures. These patterns are reminiscent of what we saw for school districts, with higher proposal and passage rates in the Bay Area. Distribution of Bond Measures Across Municipalities The vast majority of municipal bond measures were proposed and passed by very few cities. San Francisco proposed 27 measures of which 16 passed, and Los Angeles proposed 15 of which nine passed. Table 4.4 shows that 399 cities proposed no bond measures, 51 cities proposed a single measure, 12 cities proposed two measures, six cities proposed three measures, and Berkeley and San Diego proposed four measures. As noted above, Los Angeles and San Francisco proposed more than 10 measures each. Table 4.4 Distribution of Bond Measures Proposed by Cities, 1986–2000 No. of Measures Proposed 0 1 2 3 or 4 10+ Total or average No. of Cities 399 51 11 8 2 Passage Rate (%) 37 36 49 67 471 39 51 Only 25 cities, or 5 percent, had one successful bond measure, and only four cities (San Francisco, Los Angeles, Berkeley, and Oakland) passed three or more (Table 4.5). Berkeley and Oakland held four and three elections, respectively, and all seven bond measures passed. Table 4.5 Distribution of Bond Measures Passed by Cities, 1986–2000 No. of Measures Passed 0 1 2 3+ Total or average No. of Cities 438 25 4 4 Passage Rate (%) 85 92 83 471 39 Determinants of Municipal Government Bond Elections and Capital Revenues We next examine the characteristics of the cities that had successful bond elections (Table 4.6). Our sample is limited to 348 cities for which we have demographic information. The cities that passed bond measures are larger than cities that did not propose a bond election or were unsuccessful. They tend to have a lower percentage of homeowners in their cities, and they tend to be in counties with fewer special districts. As noted above, they also tend to be in the Bay Area. We have limited information on municipalities’ capital expenditures over time spent. As with school districts, we aggregate capital expenditures for municipalities for the period between 1992 and 2000. The 29 cities that proposed and passed a bond measure spent almost twice as much as those that proposed none ($2,390 and $1,260, respectively, on a per capita basis), which in turn spent slightly less than cities that proposed but were unsuccessful at passing a bond measure ($1,440). As we found for school districts, it seems that passing a bond measure is a major force behind the undertaking of capital spending projects. 52 Table 4.6 Demographic and Fiscal Characteristics of Cities, by Bond Measure Experience, 1986–2000 Characteristic Did Not Total Propose No. of cities 348 287 Capital Expenditures Per capita capital expenditures, 1992–2000, $ 1,347 1,260 Demographics Average population Density (population/sq. mi.) Real per capita income, $ % living in same house for 5 years % homeowner % over age 65 % nonwhite No. of special districts in county, 1997 62,460 4,451 22,689 45.5 57.4 11.6 27.1 55 41,419 4,466 21,969 45.8 57.6 11.5 27.4 58 Proposed and Did Not Pass 32 1,440 65,240 3,761 26,602 44.0 60.2 12.5 24.5 43 Proposed and Passed 29 2,390 267,631 5,056 25,495 44.2 53.0 12.5 27.0 43 NOTES: Capital expenditures data are from Cities Annual Report, published by the California State Controller’s Office. Expenditures in the 1992 to 2000 period are aggregated in real 2000 dollars. Demographic information is calculated from 1990 Census data. Municipal Tax Elections Over the last 15 years, California municipalities have proposed 586 tax measures. Taxes and fee elections were most often held to fund either general government services or new emergency 911 services (Table 4.7). Tax measures have similar passage rates across functions, with measures designed to fund general government passing slightly more often than other measures. Recall that general tax measures require a simple majority vote, whereas special taxes require a two-thirds majority vote. Thus, the similar passage rates result because although general taxes usually receive a smaller percentage of yes votes, they need a smaller majority to pass. Proposed tax measures for municipal finances have also taken many forms including parcel taxes, sales taxes, and specific taxes on utilities, hotel rooms, or new construction (Figure 4.3). Almost 40 percent of identified new taxes on local ballots were parcel taxes (200 of the 528 tax 53 Table 4.7 Number of Tax Measures Proposed and Passed, by Function, 1986–2000 Function General government Fire, police, jails Hospital and emergency services Recreation and parks Library Transportation Flood control Buildings Other No. of Measures Proposed 321 68 86 44 22 19 7 8 11 Passage Rate (%) 50 44 49 34 45 37 43 50 45 Total or average 586 47 250 200 Number of measures 150 100 50 0 Parcel Hotel Sales Consumer Business Missing Figure 4.3—Number of Fiscal Measures, by Type measures with identified type). Unlike property taxes, which are based on property value and are limited by law to 1 percent except to pay back bond measures, parcel taxes are not legislatively restricted. City parcel taxes are levied most often as a dollar amount per property (as in 146 of the 200 identified measures), occasionally listing different rates for 54 commercial or multiunit buildings (28 times). Fifty of the measures were for a limited amount of time—most frequently for seven years. Thus, city parcel taxes were typically passed as permanent measures in contrast to school district parcel taxes, which expired after a set amount of time. The average amount listed was $100, but a few cities proposed large taxes that were $500 or more. The median amount proposed was $50. Parcel taxes raise less money than property or sales taxes. An example of a typical parcel tax is one that was passed by multiple cities in Marin County for emergency services in 1994 and then renewed for another four years in 1998. These taxes were for paramedic services, and the $30 per parcel raised $150,895 in 1998 in Corte Madera (about $17 per capita). Similarly, an emergency service tax of $0.008 per square foot passed in Berkeley in 1998 and annually raises $2.1 million (about $20 per capita). Municipalities were next most likely to pass hotel taxes. Hotel taxes were proposed 127 times in 100 cities. These measures would often introduce a new tax or raise existing rates 2 or 3 percentage points. San Francisco and Los Angeles have the highest rates, at 14 percent. Burlingame raised $2.8 million per year when it increased its tax from 8 to 10 percent (about $100 per capita). The same percentage increase in San Mateo increased its 1998 revenues by $3.9 million ($42 per capita). Hotel tax revenues made up 8 percent of San Mateo’s 1998 general fund revenue. In 2000, Santa Rosa estimated that increasing its hotel tax by 3 percent from 9 to 12 percent would raise revenues by $900,000 ($6 per capita). Thus, the amount of money raised from hotel taxes varies depending on the rate and the number of rooms in a municipality and the vacancy rates. In the current economic downturn, municipalities are beginning to propose decreasing hotel taxes as a way to make their jurisdictions more attractive to travelers. Sales taxes were used by far fewer cities and were mainly proposed for general government services (eight times), public safety (five times), or transportation improvement (three times). Consumer taxes include mainly utility taxes, such as gas, electricity, and telephone services, and they usually fund general government activities. Business taxes usually take the form of business license taxes, although they also include taxes on admission fees to parks, libraries, or sporting events. Like consumer 55 taxes, they are mainly used to fund general government activities. Figure 4.3 lists numbers of measures by type. Passage rates also varied widely across types of taxes proposed, with hotel taxes and business taxes passing over half the time. Parcel taxes and consumer taxes and fees passed only 30 to 40 percent of the time (Figure 4.4). 100 90 80 70 Passage rate, % 60 50 40 30 20 10 0 Parcel Hotel Sales Consumer Business Figure 4.4—Passage Rate of Fiscal Measures, by Type Tax Measures Since Passage of Proposition 218 The number of tax measures proposed by city governments peaked in 1996—following the resolution of the uncertainty concerning the need for voter approval for general taxes and the passage of Proposition 218. Passage rates also increased in recent years. Recall that 1996 was the year that the court confirmed the legality of Proposition 62 and Proposition 218 was passed by state voters. Proposition 218 expanded voter requirements for user fees and confirmed voter approval requirements for general taxes. Indeed, many local governments had simultaneous elections with Proposition 218, gaining voter confirmation for taxes or fees that had been passed in prior years. We examine the number of elections that occurred before 1996, in 1996–1997, and after 1997 (Table 4.8). Most of the elections since 1998 (70 percent) were for general taxes rather than special taxes, reflecting the new requirements 56 Table 4.8 Number of Tax Measures Proposed and Passed, by Timing All taxes Before 1996 In 1996–1997 After 1997 No. of Measures Proposed 261 168 157 No. of Passage Measures Rate (%) per Year 41 33 55 84 50 52 Total or average 586 47 45 General government Before 1996 In 1996–1997 After 1997 130 50 16 82 50 41 109 51 36 Total or average 321 50 25 under Proposition 218. In subsequent years, the number of local elections stayed higher than it had been before 1996, reflecting the need for voter approval for more revenue sources. The second column in Table 4.8 shows that as use of the ballot box increased, so did passage rates, which peaked in the period surrounding Proposition 218. Also note that passage rates for general taxes remained constant with about half of these measures passing over our entire sample period. Regional Patterns in Municipal Tax Elections As with bond measures, we find that there were more tax elections in the Bay Area and the southern region than in the other regions of the state. There were also more elections in the Bay Area on a per city basis. The passage rates for tax measures varied dramatically across regions. Taxes were passed almost two-thirds of the time when they were proposed in the Bay Area, whereas in Southern California and coastal counties they passed less than 40 percent of the time (Table 4.9).3 ____________ 3Similar patterns exist across the different counties within the regions. Appendix Table D.1 includes county-level statistics on the number of cities in a county, the number of municipal elections held, and passage rates. 57 Table 4.9 Number of Tax Measures Proposed and Passed, by Region, 1986–2000 Region Northern Bay Area Valley Coastal Southern Total or average No. of Cities 62 100 75 42 192 471 No. of Measures Proposed 79 178 86 62 181 586 Passage Rate (%) 46 63 49 37 35 47 Distribution of Tax Measures Across Municipalities Almost half of all cities, 204 cities, had no local tax measures between 1986 and 2000, and another one-fourth had only one such measure (Table 4.10). Only 21 cities had five or more measures over this period. There is no clear relationship between passage rates and the number of times cities have gone to the ballot for financing. Table 4.10 shows that passage rates were highest for cities that used tax measures five or more times (55 percent) but were higher for cities that used them only once than for cities that used them four times (45 versus 39 percent). Of the 160 cities that successfully passed at least one new tax, 109 passed only one (Table 4.11). However, eight cities passed five or more new taxes; six of these in the Bay Area.4 Thus, municipalities used the ballot box in different ways. About half of all cities have not asked for voter approval, and of those that did place new taxes on their ballots, most passed only one. In contrast, a small group of cities repeatedly asked for, and received, voter approval to expand revenue sources. The use of the ballot box has expanded over time, with more cities asking for voter approval in the aftermath of Proposition 218. ____________ 4They are Berkeley, Larkspur, Oakland, Piedmont, Ross, and San Francisco. The other two cities that passed five or more taxes were Azusa in Los Angeles County and Isleton in the Central Valley. 58 Table 4.10 Distribution of Tax Measures Proposed by Municipal Governments, 1986–2000 No. of Measures Proposed 0 1 2 3 4 5+ Total or average No. of Cities 204 121 75 36 14 21 471 Passage Rate (%) 45 41 46 39 55 44 Table 4.11 Distribution of Tax Measures Passed by Municipal Governments, 1986–2000 No. of Measures Passed 0 1 2 3 4 5+ Total or average No. of Cities 311 109 29 9 5 8 471 Passage Rate (%) 0 71 77 89 85 84 44 Determinants of Municipal Tax Elections and Current Revenues What determines which cities went to the ballot box to raise new funds? We limit our analysis to the 348 cities that were incorporated before 1972 to better measure the changing reliance on different revenues over time and because we have accurate demographic information for them. Of the 348 cities, 145 cities did not propose any tax measures between 1986 and 2000, 86 cities proposed but did not pass any tax measures, and 117 cities proposed and passed at least one measure. 59 On average, cities that passed a tax measure were larger than those that did not go to the ballot box and those that were unsuccessful in receiving voter approval (Table 4.12). Cities with higher income or with fewer special districts were also more likely to successfully pass a new tax measure. This pattern could reflect differences in who provides specific services. If a city is responsible for more public services, the amount of money needed will be larger. Cities that passed new taxes had a lower percentage of nonwhite households than those that were not successful at raising new funds. Thus, income, population size, and the racial makeup of a city seem to affect whether cities successfully pass new taxes through the ballot box. Other demographic characteristics do not seem to differ across these three groups of cities. Which factors have made cities more likely to propose or pass a new tax using the ballot measure? It may be that certain cities were better able to respond to the pressures imposed by Proposition 13 and subsequent statewide restrictions on their funding sources before Proposition 13. Given the funding formulas used in allocating property tax revenues, we would expect certain characteristics to affect which cities would turn to the ballot box. The primary effect of Proposition 13 was to cut property tax levels, which would make cities that were more reliant Table 4.12 Demographic Characteristics of Cities, by Tax Measure Experience, 1986–2000 Characteristic No. of cities Did Not Total Propose 348 145 Proposed and Did Not Pass 86 Proposed and Passed 117 Average population Density (population/sq. mi.) Real per capita income, $ % living in same house for 5 years % homeowner % registered Democrat, 1999 % over age 65 % nonwhite No. of special districts in county, 1997 62,460 4,451 22,689 45.5 57.4 57.8 11.6 27.1 55.2 50,121 4,922 21,358 46.4 57.0 57.7 11.0 30.7 63.3 49,425 4,180 20,120 43.2 57.1 57.1 12.0 26.3 54.1 87,335 4,066 26,227 46.0 58.3 58.5 12.1 23.3 46.1 NOTE: Data are calculated from the 1990 Census unless otherwise noted. 60 on property tax revenues more likely to pass new taxes. In contrast, cities that had high levels of revenues from other sources before passage of Proposition 13 may be in better fiscal shape. We present information on average revenue levels and sources of revenues for the complete group of cities in our sample and we also split the sample into three subsamples based on tax measure experience. Cities that eventually passed a tax measure had similar levels of revenues before the passage of Proposition 13 to those that did not propose a tax measure, whereas the group of cities that proposed but did not pass a measure had lower levels of revenues even in the 1970s (Figure 4.5). These differences in per capita revenues increased following passage of Proposition 13. Cities that had been negatively affected went to the ballot box; those that were successful at passing a ballot measure maintained revenue levels on par with cities that did not propose new taxes; and those that were unsuccessful faced lower levels of revenues. Thus, cities that have not passed new taxes have historically spent less money than other cities, differences that expanded after Proposition 13. Did cities that went to the ballot box have a different tax structure in place before Proposition 13, and how did revenue structures change 1,200 1,000 Did not propose Proposed and did not pass Proposed and passed Revenue dollars (2000) 800 600 400 200 0 1972 1977 1982 1987 1992 1997 Figure 4.5—Average Per Capita General Revenue, by Measure Outcome, 1972–1997 61 following the limitations on property tax revenues? To answer these questions, we examine average revenue structures before and after Proposition 13 (Table 4.13). In 1972, before Proposition 13, cities that would eventually succeed at passing new tax measures had substantially more of their revenues coming from property taxes than cities that did not propose tax measures. From 1977 to 1982, property taxes per capita Table 4.13 Fiscal Characteristics of Cities, by Tax Measure Experience, 1986–2000 Number of cities General revenue Property tax Intergovernmental revenues Fees and assessments General revenue Property tax Intergovernmental revenues Fees and assessments General revenue Property tax Intergovernmental revenues Fees and assessments General revenue Property tax Intergovernmental revenues Fees and assessments General revenue Property tax Intergovernmental revenues Fees and assessments General revenue Property tax Intergovernmental revenues Fees and assessments Total ($) 348 1972 616 146 167 138 1977 792 173 254 155 1982 747 113 175 240 1987 864 129 173 299 1992 959 191 147 353 1997 982 164 154 365 Did Not Propose 145 635 131 174 147 813 168 255 165 769 116 169 250 886 126 178 306 1,007 191 149 385 1,010 161 154 384 NOTE: Amounts are in constant year 2000 dollars. Proposed and Did Not Pass 86 Proposed and Passed 117 568 627 129 177 155 167 128 134 732 810 136 205 242 261 145 151 683 766 86 130 176 184 218 245 777 902 101 154 169 171 269 310 848 981 152 220 137 153 313 342 852 1,043 137 188 138 168 320 374 62 declined dramatically for all cities, however, and as would be expected, cities that eventually passed a measure had a greater decline in these funds. As these cities successfully passed new measures including parcel taxes, their funds increased. The group of cities that were unsuccessful at passing new taxes consistently had the lowest amount of property tax revenues. Cities that did not propose ballot measures had a more diversified tax base to start with and became increasingly reliant on fees and assessments to raise funds. Note that over time, on average, all cities raised more of their money from fees and miscellaneous charges. This pattern occurred in other states as well but was more dramatic in California. Indeed, it was precisely this increased reliance on fees that led to placement of Proposition 218 on the ballot.5 In the prior section, we showed that cities that succeeded in passing a measure were larger and contained somewhat wealthier households than those that failed to pass new taxes or those that did not propose any new tax measures. They were also more reliant on property taxes historically and spent more money per capita than other cities. Cities that proposed but failed to pass new tax measures were somewhat poorer and had historically lower spending levels than the other two groups of cities. However, examining differences across average spending levels and characteristics does not clarify which factors are most important in driving cities to the ballot box. We therefore turn to a more nuanced examination of the relationship between city demographics and the amount of revenues raised by different cities (regression results are shown in Appendix Table D.2). To examine the estimated effects of these factors on the probability of proposing or passing at least one measure, we do a similar exercise to the one carried out for school districts. Cities that had higher levels of revenue in 1977 were less likely to propose new tax measures than those with lower levels of revenue, even controlling for the other characteristics of the city. We explore how changing city characteristics, such as household income or city population, affects the predicted probability of proposing or passing at least one tax measure for a given city, by examining the effect of changing a single characteristic (Table 4.14). For example, an ____________ 5See Doerr (2000). 63 Table 4.14 Estimated Change in Probability of Proposing and Passing Tax Measures Average city Per capita general revenue % of revenues from property tax Density % registered as Democrat % in the same house for 5 years No. of special districts Probability Probability of Probability of of Passing Proposing Passing If Proposed 63.7 35.6 57.6 Low High Low High Low High 66.0 60.9 36.9 34.0 56.6 58.9 61.2 66.8 30.3 42.9 50.9 65.9 66.7 58.0 39.5 28.8 60.7 51.8 57.1 70.3 29.8 42.1 53.4 62.0 68.3 57.9 36.7 34.4 55.0 60.8 68.7 51.0 40.5 25.1 60.4 51.0 NOTES: Low values correspond to the 25th percentile and high values to the 75th percentile of each variable. See Appendix Table D.3 for the median, 25th, and 75th percentile values of variables used in these simulation results. average city6 had a 64 percent chance of placing at least one measure on a ballot and a 36 percent chance of passing a tax measure over this period. If 1977 per capita revenue had been $900 instead of $700, the probability of placing a measure on the ballot would decrease to 61 percent, and the probability of passing to 34 percent.7 The reliance on the property tax plays a more dramatic role. If the average city had been highly reliant on property tax revenues and raised 26 percent of its funds in 1977 from the property tax, its probability of having an election would be 67 percent, and its chance of passing a new tax would be 43 percent. If the city had been less reliant on the property tax and property tax funds made up only 14.5 percent of its funds, its probability of proposing a new tax would be 61 percent and its probability of passage would drop to 30 percent. Thus, being more reliant on the property tax in 1977 increased the probability of passing a new tax measure by 40 percent. ____________ 6An average city is one with the median level of population, percentage homeowners, and other demographic characteristics listed in Table 4.13. 7In simulating the influence of a given variable, we will change the average characteristic to a low or high level; the low level corresponds to decreasing the variable in question from the average level to the value at the 25th percentile; increasing the characteristic entails a change to the 75th percentile. 64 The liberalness of voters in a city also plays a role in whether a new tax is proposed and passed. A city with an electorate of 67 percent registered Democrats on average proposes at least one ballot measure 70 percent of the time and passes at least one tax 42 percent of the time. In contrast, if the electorate was only 47 percent Democrat, a ballot measure is proposed 57 percent of the time and passed about one-third of the time. Do differences in city characteristics drive our regional differences? Is the higher use of ballot measures found in the San Francisco Bay Area related to the more liberal attitudes of voters and an earlier reliance on the property tax? To answer these questions, we examine differences in regional patterns once we control for other differences in city characteristics (Figure 4.6). A city in Northern California, the Bay Area, or the coastal region would be predicted to propose a tax measure 70 to 75 percent of the time, with cities in the northern region passing at least one ballot measure 40 percent of the time, and half the Bay Area cities passing at least one measure. Thus, part of the increased use of ballot measures in the Bay Area is related to other characteristics. Similarly, the decreased use of ballot measures in cities in the northern counties is related to the smaller population and density in these areas. In contrast, cities in the valley and Southern California are less likely to propose or pass a new tax when other differences are controlled for.8 Thus, we find that cities that were more reliant on property taxes before Proposition 13 are more likely to pass and propose new taxes, as are cities in the Bay Area and those with larger populations and more registered Democrats. Up until now, we have explored what makes a city more likely to go to the ballot box. We now turn to the effects of these decisions. First, we will examine whether the demand for revenues has changed systematically over time in ways related to passage of Proposition 13. Second, we explore whether the gaps in average revenues for cities that ____________ 8Appendix Table D.2 presents the regression coefficients from these models, with information on the effect of other demographic controls, and Table D.3 presents information on low, average, and high values of our different city characteristics. 65 Probability, % 100 90 80 70 60 50 40 30 20 10 0 Northern Bay Area Valley Proposing Passing Coastal Southern Figure 4.6—Estimated Probability of Proposing and Passing a Tax Measure, by Region did not propose, proposed but did not pass, and proposed and passed tax measures can be ascribed to differences in demographic characteristics of cities. We estimate demand for revenue models as we did for school districts presented in Chapter 3 (Appendix Table D.4). That is, we explore how per capita revenue levels are related to the size and density of cities and characteristics of their residents. We find similar patterns over time for most variables except for the role played by household mobility. Average revenue levels became more dependent on the percentage of a city’s population that had lived in the same house for more than five years after passage of Proposition 13. This result is not surprising, because before Proposition 13 was passed, assessed values were brought up to market rates on a periodic basis, whereas after Proposition 13 passed, assessed values were brought up to market rates only when property was sold. The effect of limited mobility on revenues increased beginning in 1987. We estimate that in 1997, in a city that had had a turnover rate of 40 percent in 1990, average revenues per capita would have been $796, whereas in a city with an average 66 turnover rate of 45 percent, average revenues per capita would have been $838.9 We next examine the role that proposing and passing at least one tax measure plays in the level of revenues after controlling for city demographic characteristics. We therefore examine how revenues would change for an average city10 if it had never proposed a tax election, had proposed and passed at least one tax measure, or had proposed but never passed a new tax measure. In 1997, a city with median demographic characteristics that had never proposed a tax measure had average per capita revenues of $874; a city that had proposed and passed a measure had virtually identical revenues per capita of $878; and a city that had proposed but never passed a ballot measure had revenues of only $774 (Figure 4.7). Controlling for demographics decreases the inequality 1,200 1,000 Did not propose Proposed and did not pass Proposed and passed Revenue dollars (2000) 800 600 400 200 0 1987 1992 1997 Figure 4.7—Estimated Real Per Capita General Revenue for a City with Average Demographics ____________ 9The importance of reassessing property is affected by how much appreciation occurs in house prices. Sheffrin and Sexton (1998) analyze the relationship between the market value and assessed value of property since the passage of Proposition 13 and how this relationship has affected property tax administration in California. They find that declines in property values helped to reduce the inequity in the property tax system during the early 1990s. 10That is a city with median characteristics. 67 between cities that have never proposed elections and those that proposed but did not pass a tax measure but does not completely explain these differences. Thus, it seems that the difference in city characteristics only partly explains differences in spending. Summary Since Proposition 13 was passed in 1978, very few city governments have proposed bond measures and most who did passed only one. The notable exceptions to this are San Francisco and Los Angeles. The predominant tax proposals are parcel taxes and hotel taxes to fund general government services. There has been an increased reliance on ballot measures in recent years following passage of Proposition 218. We also found that passage rates have increased. Municipal governments have become less reliant on the property tax, but overall per capita revenues have not declined. When we examined which cities went to the ballot box and which cities approved new tax measures, we found that cities that were historically more reliant on property taxes were more likely to ask for and receive authorization to implement new tax measures. We also found that proposal and passage rates were more likely in cities with a high percentage of registered Democrats. Denser cities and cities in the Bay Area were also more likely to ask for and receive voter approval for new tax measures. We also found that revenue levels have become increasingly dependent on household mobility, with cities that have a smaller population living in the same house for five years on average raising more money, because of higher levels of reassessment of property to market value. Finally, even after controlling for city characteristics, we found that revenue levels were lower for cities that had proposed but had failed to pass new tax measures, whereas cities that had successfully asked voters for new tax authority had similar spending levels to cities that did not propose new measures. 68 5. County and Special District Use of the Ballot Box In California, 4,628 non–school district jurisdictions can receive financing from local ballot measures. We have information on 1,461 elections that occurred in these jurisdictions in the period from 1986– 2000. Municipal governments proposed about half of these elections. County governments proposed 14 percent of these elections and special districts propose the remainder.1 In this chapter, we examine measures proposed by counties and special districts and explore how these governments used the ballot box to raise funds. Because of the differences in patterns found across regions in the state, we then look at the combined use of fiscal ballot measures across counties, cities, and special districts. The advantage in examining the use of ballot measures across all non–school districts is that we can make comparisons across services that are funded by different levels of governments. County Use of the Ballot Box County governments play a variety of roles, the two main ones being to act as an agent of the state, providing such specific services as social service programs and court services, and providing municipal services for unincorporated areas, or for counties with few municipalities, throughout the county. These include police, fire, trash collection, and many other services that resemble those provided by municipalities. To investigate how large a role a county plays in providing municipal services, we examine the percentage of local revenues controlled by the county (as compared to municipalities or special districts). In more rural ____________ 1For a discussion of the long-term trends in California’s local government structure and the possible effects of Proposition 13, see Lewis (1998). 69 counties concentrated in the northeastern region of the state, most nonschool district local expenditures are controlled by county governments, whereas more urbanized regions in the state rely more on municipal governments to provide services. Figure 5.1 maps the percentage of expenditures controlled by counties in 1997.2 In seven counties in the northern region and the Central Valley, over 80 percent of expenditures are controlled by the county governments. Recall that many of these counties were shown in Chapter 4 to have few municipal governments and also had very few ballot measures proposed by municipalities. 24–50 51–65 66–80 81–100 Figure 5.1—Percentage of 1997 Direct Expenditures Controlled by Counties ____________ 2Appendix Table E.1 includes county statistics for Figures 5.1, 5.4, 5.5, and 5.6. 70 County Bond Elections We consider a measure to be countywide if it was voted on by residents throughout the county. If a measure was applicable only to a small portion of the county, we classified the ballot measure as a special district election. There were relatively few countywide bond measures in our sample.3 We have information on 25 bond measures, all but three of which were proposed before 1996. Of the 25 measures proposed by county governments, eight of the nine measures under “fire, police, jails” were proposed to fund the construction or modernization of jail facilities (Table 5.1). County bond measures were proposed mainly in northern counties, the Bay Area, and southern counties (Table 5.2). Again, the increased ballot box use in northern counties partly reflects the lack of municipal governments in these counties. Table 5.1 Number of Bond Measures Proposed and Passed by Counties, by Function, 1986–2000 Function Fire, police, jails Hospital and emergency services Recreation and parks Library Other No. of Measures Passage Proposed Rate (%) 9 22 30 5 20 3 33 5 40 Total or average 25 24 County Tax Elections Countywide taxes were usually proposed by more rural counties to provide additional funds for general government services. About onethird of county taxes were for general government services and onequarter were proposals to fund emergency services, which include 911 ____________ 3Note that San Francisco bond measures were included under city measures rather than under county measures. 71 Table 5.2 Number of Bond Measures Proposed and Passed by Counties, by Region, 1986–2000 Region Northern Bay Area Valley Coastal Southern Total or average No. of Counties 22 8 15 6 6 57 No. of Measures Proposed 6 9 2 1 7 Passage Rate (%) 17 11 50 0 43 25 24 services and additional paramedic, police, or fire protection (Table 5.3). Passage rates also varied across functions, with the highest passage rates occurring for transportation measures. Similar to the results we found for cities, recreation and park taxes had the lowest passage rates of any specific function taxes. County governments also asked for a multitude of different tax types, including sales, hotel, and parcel taxes (Figure 5.2). The tax type Table 5.3 Number of Tax Measures Proposed and Passed by Counties, by Function, 1986–2000 Function General government Fire, police, jails Hospital and emergency services Transportation Recreation and parks Library Other Total or average No. of Measures Proposed 66 24 18 29 8 25 11 Passage Rate (%) 29 13 44 45 25 28 64 181 33 72 Number of measures 90 80 70 60 50 40 30 20 10 0 Parcel Hotel Sales Consumer Business Missing Figure 5.2—Countywide Measures, by Type of Tax most often requested at the county level was a sales tax increase and most initiatives proposed were to raise the sales tax by one-half cent (58 times), one-quarter cent (16 times), one cent (twice), or one-eighth cent (three times). Eighteen of these measures were for an explicit amount of time, usually 15–20 years. The lower passage rate found for counties is in part due to counties proposing sales taxes in multiple elections until one passes. Because a sales tax is broad-based, it raises considerably more revenue compared to a parcel tax or a transient occupancy tax. Passage rates are shown in Figure 5.3. Note that although most county tax measures had very low passage rates (33 percent), voters were very likely to pass such consumer taxes (77 percent) as utility fees and garbage collection charges. These passage rates are very different from the ones found for city tax measures—countywide hotel taxes and other business taxes had much lower passage rates than those for municipal taxes. Similar to what we found for cities, the number of measures proposed by counties peaked in the period surrounding Proposition 218. Before 1996, 13 measures a year were proposed, the number peaked at 18 per year during the 1996–1997 period, and fell to 15 in 1998–2000 73 Passage rate, % 90 80 70 60 50 40 30 20 10 0 Parcel Hotel Sales Consumer Business Figure 5.3—Passage Rate of Countywide Measures, by Type of Tax (Table 5.4). The increase in use corresponds to the period surrounding passage of Proposition 218, which required voter approval for general taxes and user fees. Table 5.4 Number of Tax Measures Proposed and Passed by Counties, by Timing Before 1996 In 1996–1997 After 1997 Total or average No. of Measures Proposed 100 35 46 181 Passage Rate (%) 32 43 26 No. of Measures per Year 13 18 15 33 14 Regional Patterns in County Tax Measures Almost one-third of county taxes were proposed in the northern region of the state, where 30 of the 58 measures proposed were to fund general government services (Table 5.5). Emergency and library service measures were proposed by counties in most regions. Library measures 74 Table 5.5 Number of Tax Measures Proposed by Counties, by Region and Function Function General government Fire, police, jails Hospital and emergency services Transportation Recreation and parks Library Other No. of Measures Proposed Northern Bay Area Valley Coastal Southern 66 30 14 14 4 4 24 5 961 3 18 4 29 6 83 25 6 11 4 554 0 774 5 121 1 566 2 330 1 Total 181 58 44 43 20 16 were the only type proposed more often at the county level than at the municipal level, with counties proposing 25 library tax measures and cities proposing 22. Overall, county measures passed about one-third of the time; however, there is wide variance in passage rates across regions and function (Table 5.6). Passage rates for county measures were lower in the northern counties (21 percent) and the Central Valley (26 percent). In contrast, counties in the Bay Area, coastal counties, and southern counties passed countywide measures twice as often, with Table 5.6 Passage Rate of Tax Measures, by Region and Function Function General government Fire, police, jails Hospital and emergency services Transportation Recreation and parks Library Other Average Passage Rate (%) Northern Bay Area Valley Coastal Southern 29 27 57 14 25 0 13 0 11 17 0 33 44 0 45 0 25 0 28 33 64 50 80 40 50 N/A 57 43 75 60 0 0 100 100 20 17 33 50 67 67 N/A 100 33 21 45 26 45 44 75 passage rates around 45 percent. Overall passage rates for transportation measures were higher than for other specified measures. The overall number of county measures by function by region is small, so the disparity in passage rates across some types of measures reflects the fact that most regions had only a few elections for each specified function. Special District Use of the Ballot Box Special districts also play an important role in providing local services. They include districts that are set up to provide a certain service, such as fire or water districts, or to provide general services to a specific area of a county (CFDs) or to aid development. CFDs are often formed as part of a development agreement. Often, for development to take place local officials require that new developments pay additional fees or taxes. These occur in Mello-Roos districts and are included as CFDs in our analysis. Counties in Southern California had many more special districts than those in the Bay Area or the northern region of the state (Figure 5.4). Numerous special districts also proposed tax and bond measures through the ballot box. We have information on 527 fiscal measures placed on the ballot between 1986 and 2000. Of these ballot measures, 461 were for taxes or fees and assessments and only 66 were for bond measures. Bond Elections Held by Special Districts CFDs, water districts, and park districts had the highest number of bond elections, each with around 15 measures (Table 5.7). Park district bond measures were typically to acquire property, and water district bond measures were to fund water main construction or treatment centers. CFD bond measures also fund water projects, transportation, or the purchase of open space and thus serve a similar function to other special districts. These different bond measures had vastly different passage rates, with water district measures passing 81 percent of the time, park district bonds passing only 15 percent of the time, and the CFD district bonds passing about half of the time. 76 1–15 16–30 31–50 51–75 76–111 Figure 5.4—Number of Special Districts, 1997 The number of bond measures proposed declined after 1996, similar to the pattern found for counties. However, passage rates increased after 1996—similar to the patterns we found for school districts and cities (Table 5.8). However, there were only eight special district bond elections proposed. Regional Patterns in Special District Bond Elections Unlike patterns found for other bond measures, special districts in coastal counties proposed bond measures most overall and per special district; these measures had a passage rate similar to that found in the Bay Area (Table 5.9). Passage rates across all regions except the southern counties were higher for special district bond elections than for bond elections proposed by cities or counties. 77 Table 5.7 Number of Bond Measures Proposed and Passed, by Type of Jurisdiction Jurisdiction Counties Cities Special districts CFD Fire, police, jails Recreation and parks Transportation Hospital Library Flood control Water district Other Total or average No. of Measures Proposed 25 142 66 17 2 13 1 10 1 2 16 4 Passage Rate (%) 24 49 50 47 100 15 0 40 100 100 81 0 233 46 Table 5.8 Number of Bond Measures Proposed and Passed by Special Districts, by Timing Before 1996 In 1996–1997 After 1997 No. of Measures Proposed 58 3 5 No. of Passage Measures Rate (%) per Year 47 7 67 2 60 2 Total or average 66 49 5 Tax Elections Held by Special Districts The vast majority of the tax measures proposed by special districts were parcel taxes. CFDs proposed 150 tax measures, for a variety of general and specific government services including road repair, fire protection, and public works (Table 5.10). These fiscal measures passed 41 percent of the time. Fire districts proposed 139 measures, and they 78 Table 5.9 Number of Bond Measures Proposed and Passed by Special Districts, by Region Region Northern Bay Area Valley Coastal Southern Total or average No. of Districts 707 228 772 180 330 2,217 No. of Measures Proposed 9 11 10 24 12 Passage Rate (%) 75 55 44 54 25 66 50 Table 5.10 Number of Tax Measures Proposed and Passed, by Type of Jurisdiction Jurisdiction Counties Cities Special districts CFD Fire, police, jails Recreation and parks Transportation Hospital Library Flood control Water district Other No. of Measures Proposed 181 586 461 150 144 46 26 32 14 13 13 23 Passage Rate (%) 33 47 46 41 51 35 50 50 50 46 77 39 Total 1,228 45 paid for fire protection services or emergency services including 911 programs. Fire districts had one of the highest passage rates, with proposals passing over half the time. Recreation and park districts proposed 46 measures to maintain existing park or recreation areas and, similar to patterns found for city and county measures to fund recreation 79 areas, these measures were most likely to fail, passing slightly more than one-third of the time. Even though water districts proposed only 13 measures, almost 80 percent of these measures passed. The other district category consists of special district types that proposed fewer than 15 measures and include utility districts among others. Examining ballot measures across special districts before and after the passage of Proposition 218, we find that proposals stayed constant on an annual basis with an average of about 35 tax measures being proposed per year throughout the period (Table 5.11). This is markedly different from what we found for cities and counties and reflects the fact that special districts consistently needed to gain voter approval throughout the 1986–2000 period. This is due to the classification of all special district taxes as special taxes and therefore subject to voter approval following Proposition 13 in 1978. Table 5.11 Number of Tax Measures Proposed and Passed by Special Districts, by Timing Before 1996 In 1996–1997 After 1997 Total or average No. of Measures Proposed 287 71 103 461 Passage Rate (%) 44 58 43 No. of Measures per Year 36 36 34 46 35 Regional Patterns in Special District Tax Elections Figure 5.5 maps the number of tax elections held by special districts between 1986 and 2000. Note that special districts in five counties, especially in the southern region and the Bay Area, proposed more than 20 measures over this period. In three counties, no special districts proposed measures, and 14 counties had a passage rate of less than 25 percent for these elections (Figure 5.6). The different patterns in proposal and passage rates across different areas of the state may be caused by differences in the types of districts. 80 0–5 6–10 11–20 21–40 41–51 Figure 5.5—Number of Tax Measures Proposed by Special Districts For all regions, the special districts proposing the most tax measures were emergency service and CFDs (Table 5.12). The Bay Area had the most transportation district elections, and there were more recreation and park measures placed on the ballot in the northern region of the state. Bay Area special districts had higher passage rates than other regions of the state across types of districts (Table 5.13). Northern counties had higher passage rates for emergency service districts than for measures proposed by other types of districts; these measures passed 50 percent of the time. Thus, part of what caused the lower passage rate overall in the northern counties was the larger percentage of measures to fund recreation and park services in these counties. 81 No special district measures 0–25 26–50 51–75 76–100 Figure 5.6—Passage Rate of Tax Measures Proposed by Special Districts, Total Table 5.12 Number of Tax Measures Proposed, by Region and Type of Special District Type of District CFD Fire, police, jails Hospital and emergency services Transportation Recreation and parks Library Water district Flood control Other Total No. of Measures Proposed Northern Bay Area Valley Coastal Southern 150 50 37 17 6 40 144 49 30 27 11 27 32 12 3 12 2 3 26 3 14 46 21 16 14 4 3 13 0 5 13 3 7 23 9 4 42 33 22 22 02 44 3 3 3 4 1 2 461 151 119 71 34 86 82 Table 5.13 Passage Rate of Tax Measures, by Region and Type of Special District Type of District CFD Fire, police, jails Hospital and emergency services Transportation Recreation and parks Library Water district Flood control Other Passage Rate 41 51 50 Northern Bay Area Valley Coastal Southern 46 51 41 17 30 51 60 37 73 48 50 100 50 0 33 50 0 64 25 0 100 35 19 63 33 33 0 50 25 67 50 50 67 77 N/A 100 100 0 75 46 33 43 N/A 50 100 35 30 25 0 50 100 Average 46 41 59 39 41 43 Ballot Use Across Different Types of Governments How does use vary across the state once differences in municipal structures are accounted for?4 Does the higher use of ballot measures by county governments in northern counties lead to aggregate use more like that found in other areas of the state? Our hypothesis is that, when looking at all non–school district governments as opposed to municipalities only, use of the ballot will expand in the northern region, where there are fewer city governments, and in the southern region, which is more dependent on special districts. We do find that use of the ballot box has increased in the northern counties. Surprisingly, there is a decline in the percentage of ballot measures proposed in Southern California as compared to when we restricted our analysis to municipal ballot measures. The percentage of measures in the Bay Area, more reliant on city governments, has also declined from 35 percent of ballot measures to 30 percent. The regional use of fiscal ballot measures can be found in Table 5.14. ____________ 4We exclude school districts from our aggregate analysis. This is due to the distinct uses for school district funds and the fact that no other level of government generally provides educational services. This information is also related to preliminary calculations done in McGuire and Rueben (1997). 83 Table 5.14 Number of Measures Proposed and Passed, by Region Region Northern Bay Area Valley Coastal Southern No. of Measures Proposed Total Bond Tax 311 20 291 419 82 337 219 18 201 152 36 116 360 77 283 Passage Rate (%) Total Bond Tax 40 45 39 58 56 59 39 28 40 42 50 40 38 38 38 Total or average 1,461 233 1,228 45 46 45 Marin County had the highest number of tax measures with 94 and a very high passage rate of 61 percent. Los Angeles County also had a high number of measures, 88, but a much lower passage rate of 40 percent. Alameda County had 71 tax measures and passed 72 percent. San Diego had 60 and passed 47 percent. Contra Costa and San Bernardino had 54 and 52 measures, respectively, but passed 37 and 33 percent. Twenty counties had fewer than 10 tax measures on the ballot (Figures 5.7 and 5.8).5 Thus, Bay Area counties and southern counties had more elections overall and overall passage rates were highest in the Bay Area. Do counties with more types of governments propose ballot measures more often and what leads to the differences in ballot use? Several factors tend to be associated with the variation in the use and passage of fiscal measures across counties. We ran regressions to examine the dependence of different counties on the ballot box. These regression results can be found in Appendix Table E.3. We controlled for similar factors to those considered in Chapter 4 when examining passage rates for cities. We find that the number of governments in a county increases the number of ballot measures proposed. We predict that for every additional government in a county, the number of tax proposals will increase by 18 percent. Whereas, on average, a county has 47 non– school district governments and proposes 21 tax measures, we estimate ____________ 5Appendix Table E.2 includes county-level statistics for Figures 5.7 and 5.8. 84 1–10 11–19 20–39 40–59 60–94 Figure 5.7—Number of Total Tax Measures Proposed, by County that if the number of governments increased by 20 the number of ballot measures would have increased by 3.6, in the 1986–2000 period. We also find that the predicted number of measures increases with population and with average county personal income. We find a smaller but still positive relationship between the predicted number of successful ballot measures and the number of governments in a county. We predict that an additional 20 governments will increase the number of successful tax measures by only one. Thus, although the average county passes nine measures, an increase of 20 local governments leads to successfully passing 10 measures. We also find that the percentage of registered Democrats in a county increases the number of passing measures. If we increase the percentage of registered Democratic voters by 10 percentage points, we predict an additional 3.4 successful tax measures. 85 0–25 26–50 51–75 76–100 Figure 5.8—Passage Rate of Tax Measures Proposed, by County Does proposing more ballot measures lead to more passed measures, or is it an indication that a government is putting the same measure on the ballot multiple times? On average, for every additional proposed measure, the number of successful measures increases by about one-half. Once we control for the number of measures proposed, the influence of the percentage of voters who are Democrats diminishes. This is partly due to the increased number of ballot measures proposed in counties that have a higher percentage of registered Democrats. Once we control for other county characteristics, we find that proposal and passage rates across regions are no longer statistically different from each other. Thus, the makeup of the local governance structure and the difference in liberalness found across different regions seem to drive the earlier patterns we found across regions. 86 Do passage rates differ by how new money will be spent? Also, do certain types of governments seem to be more successful at passing new ballot measures for certain functions than others? The overall findings are similar to those found by type of government (Table 5.15). General government and fire, police, and emergency services were proposed most often and generally had the highest passage rates. There are differences in passage rates for measures to fund similar functions based on the level of government proposing the tax. For example, fire and emergency services provided by special districts passed 53 percent of the time, taxes proposed by cities for similar functions passed 83 percent of the time, and taxes to fund fire services at the county level passed only 20 percent of the time. Voters were also more likely to approve a new bond measure for road construction or improvements than a tax measure. Transportation taxes are usually funded in one of three ways: a sales tax increase (42 measures, which passed 45 percent of the time), a parcel tax (18 measures, which passed 61 percent of the time), or an increase in a bridge fee or toll. New taxes or fees for transportation functions also vary by type of government passing the tax. County transportation measures passed 44 percent of the time, city measures passed 37 percent of the time, and special district measures to fund transportation or road improvements passed 62 percent Table 5.15 Number of Bond and Tax Measures Proposed and Passed, by Function Function General government Fire, police, jails Hospital and emergency services Recreation and parks Library Transportation Flood control Buildings Other No. of Measures Proposed Total Bond Tax 419 11 408 256 35 221 224 17 207 179 60 119 98 26 72 103 16 87 80 36 44 24 9 15 78 23 55 Passage Rate (%) Total Bond Tax 46 45 46 43 40 44 47 41 47 31 25 34 46 58 42 50 44 51 65 75 57 42 56 33 45 52 42 Total or average 1,461 233 1,228 45 46 45 87 of the time. Transportation measures were the only type to have higher passage rates at the county than the city level. We next look at whether use of the ballot box for fiscal measures increased in response to the passage of Proposition 218. As we found with cities, we find a marked increase in the use of the ballot box in more recent years for both bond and tax measures. Note that passage rates for tax measures have remained fairly constant—with a temporary increase following Proposition 218, whereas bond elections (like those for school districts) have had higher passage rates in more recent years (Table 5.16). Thus far, we have examined different aspects of ballot measures but have not yet examined which attributes of a ballot measure may lead to passage. To examine partial effects, we ran a simple logistic regression on the probability of a tax measure passing given the attributes outlined above. These attributes include the timing of the election,6 the level of government proposing,7 the function of the measure,8 the type of measure,9 and the region. The regression results can be found in Appendix Table E.4. Table 5.16 Number of Bond and Tax Measures Proposed and Passed, by Timing Before 1996 In 1996–1997 After 1997 No. of Measures Proposed Passage Rate (%) Total Bond Tax Total Bond Tax 840 192 648 41 43 41 289 15 274 53 40 54 332 26 306 46 77 44 Total or average 1,461 233 1,228 45 46 45 ____________ 6Whether the election is held before 1996, in 1996–1997, or after 1997, and whether it is a primary general election or an off-cycle election. 7Whether it is a county, city, or special district proposing the measure. 8Whether the tax will fund general government services, fire and police services, recreation and parks, transportation, or other specified uses. 9Whether the measure is a parcel tax, a sales tax, a business tax (including hotels), or a consumer tax. 88 After controlling for changes in what is placed on the ballot, passage rates have not increased or decreased significantly since 1996. Although more measures have been proposed, these new measures are not any more or less likely to pass. This result is due to the lower passage rate required (a simple majority) being offset by higher voter preference for funding some specific and more popular functions. We find a small effect on the passage of tax measures based on the point in the electoral cycle that a measure is proposed, with measures proposed in off-cycle periods passing 51 percent of the time, as compared to passage rates of around 40 percent for tax measures in general elections and primaries held during even years (Table 5.17). We also find differences in passage rates across types of governments, even when timing, type of tax Table 5.17 Estimated Change in Probability of Passing Tax Measures Average measure Probability of Passing 41 City measure County measure Special district measure 40 32 47 Primary Off-cycle General 43 51 40 Transportation measures Park measures 56 29 Business Consumer 56 36 Northern Bay Area Valley Coastal Southern 31 58 35 39 35 NOTE: Average measure is one with mean characteristics. 89 proposed, use of tax, and region are controlled for. Controlling for all other factors, county tax measures pass 32 percent of the time, city measures pass 40 percent of the time, and special district elections pass 47 percent of the time. This pattern may be due to the more specific aspect of special district elections. Certain uses of funds also have higher passage rates all else equal. Transportation measures pass 56 percent of the time, whereas park measures pass an estimated 29 percent of the time. Similarly, after controlling for other characteristics, we find that hotel taxes and other business taxes pass 56 percent of the time and consumer taxes pass 36 percent of the time. We do not find a statistically significant difference in passage rates between sales taxes and parcel taxes, despite differences in the raw passage rates. Finally, we find that once a tax measure is proposed in the Bay Area it will pass 58 percent of the time; an average passage rate in the rest of the state is 35 percent. Summary In this chapter, we broadened our analysis to examine the use of fiscal measures by county and special district governments. Counties and special districts, like cities, proposed tax measures far more often than bond measures. Counties proposed a variety of different tax measures, including more broad-based sales tax measures, whereas special taxes almost exclusively relied on parcel tax measures. Northern counties proposed a larger percentage of county measures, reflecting the lack of other governments in these counties. County measures also faced relatively low passage rates, reflecting the broader taxes proposed and a prevalence of fiscal measures intended to provide park or open space. Following the passage of Proposition 218, county governments were more likely to place a measure on the ballot. Special district measures were used throughout the state, but they did not increase in number following passage of Proposition 218. Special districts had higher overall passage rates than city and county government measures, despite requiring a supermajority for all ballot measures. Passage rates did vary substantially by type of government, with special districts that provide popular services, such as water districts, experiencing much higher passage rates than CFDs or park districts. 90 We examined the aggregate use of taxes by non–school district governments. We find that use rates and passage rates were still higher for Bay Area governments. In aggregate, ballot measure use was higher in counties with more local governments. Special districts had the highest passage rates for measures even when we controlled for the purpose of the tax and the type of tax being proposed. This pattern occurs despite the need for a supermajority for passage of these taxes. We also found little evidence of passage rates changing after passage of Proposition 218; although more ballot measures have been proposed, passage rates have stayed relatively constant. 91 6. Policy Considerations Statewide restrictions on local governments’ ability to raise funds have required that voters play a more active role in fiscal decisionmaking. As a result, understanding how new money is raised through the ballot box becomes increasingly important. California local officials are currently required to gain voter approval to pass new bond measures for capital expenditures (two-thirds majority), special taxes (two-thirds majority), general taxes (majority), and fees and assessments (majority of homeowners, supermajority of voters). As the economy weakens and existing instruments raise less money, local officials once again will face hard decisions about how to pay for needed government services. The detailed descriptions of successful and unsuccessful ballot measures may be instructive to elected leaders as they make these hard choices. This report has examined revenue patterns of local governments over the last 30 years. California’s local governance structure is more complicated than those found in many other states. In some counties, municipal governments provide the majority of local services; in others, special districts play an increasingly visible role. Overall, California local governments, especially school districts and counties, have become more reliant on state revenue sources. This trend differs from that found in the rest of the country, where local governments more often provide services with own-source revenues. As the state faces its own budget difficulties, however, it is cutting funds for local governments and instead authorizing more local governments to raise their own funds. In the closing days of the last legislative session, Governor Davis approved a bill allowing some cities to increase sales tax rates to pay for general services pending approval of city voters. Local officials therefore need to consider what revenues they need to fund which services and whether to ask voters for new general or specific taxes. Our analysis offers some lessons to policymakers as they decide what types of tax measures to propose to raise future funds. Our findings 93 suggest that if popular programs such as transportation measures or fire protection require funding, a dedicated tax, despite the required supermajority for approval, is more likely to garner voter support than a general tax. There are limitations concerning special taxes, as these funds are earmarked for specific spending areas and therefore will reduce local officials’ flexibility. However, if municipal governments need revenues to fund less popular programs such as library or park services, they might be more successful trying to pass a general tax. General taxes, however, face different approval rates depending on what kind of tax was proposed. Hotel taxes and business taxes were passed most often by cities. However, hotel tax increases have typically been proposed during periods of economic expansion and may discourage tourism during a recession. Proposing taxes at the county level is more problematic. Although passage rates depend on the purpose of the tax, generally county tax increases passed less often than city or special district measures. County taxes faced different approval rates with hotel taxes being passed less often than parcel taxes. The preliminary evidence indicates that in the aftermath of Proposition 39, more school districts successfully passed new bond measures and raised new funds. In light of predicted enrollment increases and current estimates that one-third of schools need major repairs, this is positive news. As more school districts are successful in passing debt, it may be necessary to examine the role that assessed value currently plays in capital financing, as school districts may start hitting their debt limit caps. Depending on the outcome of that examination, state officials may want to consider raising current debt limits.1 The state is also proposing new state bonds for school construction totaling $25 billion over the next few years. Historically, school districts applying for state money needed to raise matching funds, which meant that districts with less ability to raise money would be ineligible for state aid. Possible funding alternatives include allocating revenues to school districts on a per pupil basis or instituting a power equalization program ____________ 1Brunner and Rueben (2001) examine the distribution of facility funds across districts in the 1990s. The Legislative Analyst’s Office (2001) describes one alternative state funding system, whereby state capital funds would be distributed to districts on a per pupil basis annually. 94 whereby state funds are used to bring up the capital funds of districts with lower assessed value. Fiscal policy by plebiscite is part of California’s current system. Our results show that although statewide voters have increasingly expanded the number of fiscal measures that need approval, these measures need not curtail the functions of governments. Even as government officials have been required to expand voter input, passage rates for tax measures have increased. Indeed, Proposition 39 is evidence that voters are willing to ease fiscal restrictions and support public programs, possibly with a caveat of additional accountability, if funding is going to support programs they desire. Thus, as local ballot measures are used more frequently, both state and local officials will need to evaluate how their public finances are changing and what other changes are necessary in light of new statewide laws. The indications are that local ballot measures will play an increasingly visible role, and the conversation between voters and policymakers will continue. 95 Appendix A Information on Local Measures We gathered information on tax and bond measure questions for local governments in the state from four sources: State and Local Tax and Bond Ballot Measures: Summary of Election Results by the California Debt and Investment Advisory Committee (CDIAC);1 the California Ballot Monitor: A Guide to Local Land Use and Taxation Measures by the California Association of Realtors (REALTORS); the Coalition for Adequate School Housing (CASH), which had data on school district elections; and individual counties and the Internet. The CDIAC has comprehensive data for all tax and bond measures on the general election ballots for even years from 1986–2000 and for primary election ballots from 1990. However, CDIAC did not include elections that took place during odd years or on dates other than those of primary and general elections. The REALTORS dataset complements the CDIAC to a certain extent. It provides information on elections that occur in odd years and on elections that took place on non-primary and non–general election dates during the year. It has also complete coverage of Gann override measures. However, the REALTORS data cover only the 1987–1992 period. Data from these sources are complemented with the CASH data on school facilities elections. However, again, this dataset has the limitation that it provides information on school districts only. We also collected information on off-year elections since 1996 from county websites, newspaper articles after elections, and, as much as possible, from county election authorities. The propositions that appeared in different documents always listed the same outcome, which ____________ 1CDIAC was known as the California Debt Advisory Committee (CDAC) before 1996; the committee’s name and functions were expanded in response to the Orange County bankruptcy. 97 shows some consistency among the four sources. The number of voters and percentage of the electorate voting for the measure did differ slightly among the sources, but never by more than 5 percent. The breakdown of the observations is shown in Table A.1. The principal source of tax measure information is CDIAC, with more than 50 percent of the observations coming from it. For bonds, the source of the information is divided among CDIAC, REALTORS, and CASH, although the CASH dataset covers 80 percent of the bond elections. It may be easier and clearer to see where measures came from if we look at them yearly (Table A.2). 1993 and 1995 are the least complete years, with information coming only from CASH on school elections. Information on the remaining years came from a combination of sources up until 1992 (CDIAC, REALTORS, and CASH) and after 1992 (CASH and CDIAC) or the Internet and county offices, depending on whether it was an even or odd year. Information collected from the Internet came mainly from county election departments’ websites. Those without websites or not featured in any news coverage from other voting sources (mainly San Francisco Chronicle, Los Angeles Times, or Smartvoter.com websites among others) were contacted directly. Because we have the most complete information for school districts, it is useful to look at these sources excluding school district measures. Table A.3 shows the number of measures by year and source excluding school district elections. As mentioned above, the only information we have for 1993 and 1995 came from CASH data, which means that we Table A.1 Number of Measures, by Source and Type Source Tax Bond Total CDIAC 755 289 1,044 REALTORS 276 268 544 Both CDIAC and REALTORS 184 100 284 CASH 122 429 551 Counties and Internet 150 96 246 CASH and others (school districts) 137 520 657 Total 1,487 1,182 2,669 98 Table A.2 Number of Measures, by Source, Type, and Year Year 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 Total 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 Total CDIAC 52 65 50 31 98 175 162 122 755 16 1 24 45 36 85 82 289 CDIAC and REALTOR REALTORS Tax 40 50 58 61 16 66 79 30 60 276 184 Bond 45 36 26 59 27 45 73 28 27 2 268 100 Counties and Internet 5 109 1 31 4 150 63 33 96 CASH 11 10 2 1 3 1 2 29 12 14 2 16 10 9 0 122 8 24 12 8 9 8 9 45 22 85 27 50 50 62 10 429 lose these observations when we exclude school districts from the analysis. The major source for information on taxes was CDIAC. For bonds, the major source if we exclude school elections was REALTORS. 99 Table A.3 Number of Measures, by Source, Type, and Year, Excluding School District Elections Year 1986 1987 1988 1989 1990 1991 1992 1994 1996 1997 1998 1999 2000 CDIAC 50 63 48 28 93 163 159 117 CDIAC and REALTORS REALTORS Tax 34 44 55 41 14 59 45 18 56 Counties and Internet 6 103 1 26 5 Total 1986 1987 1988 1989 1990 1991 1992 1994 1996 1997 1998 1999 2000 721 15 1 10 11 11 10 13 196 170 Bond 19 18 15 27 13 26 18 7 11 141 5 3 Total 71 102 52 8 From all these sources, we constructed our final dataset, which includes information on the date of the election, measure letter (i.e., Proposition A), region, county, authorizing agency name and type, percentage of yes and no votes, whether the measure passed, the purpose 100 of the measure, the type of tax or amount of the bond, and the source of information. To check for completeness in the dataset, we looked at cities with off-cycle mayoral elections (that is, not on primary or general election dates). We checked whether cities in our dataset that had elections on off-cycle dates were less likely to have proposed a tax measure. If that were the case, we could have been missing information on those cities. Table A.4 indicates that this is not the case. Of the 348 cities in our sample for which we have election timing information, those with offcycle mayoral elections were only slightly more likely to be in the “did not propose” tax measure category. Even though 44 percent of cities with off-cycle elections did not propose any fiscal measure in our sample, and 40 percent of cities with on-cycle elections did not, the difference was not statistically significant. Finally, to further explore election data completeness, we looked at school district elections. We wanted to examine their distribution across years and election dates (primary, general, or other). Table A.5 gives this information. School district elections were more likely to be held on a date that does not correspond to a general or primary election. Districts proposed measures outside the general/primary cycle usually in March and April. School district elections were also more likely to occur during odd years, and presidential elections happened during even years. For information on the history of measures in our sample for specific localities or types of government, contact the authors. Table A.4 Number of Cities, by Election Cycle Timing No. of Cities On-cycle Off-cycle Missing Did Not Propose 72 51 22 Proposed and Did Not Pass 52 24 10 Proposed and Passed 59 40 18 Total 183 115 50 Total 145 86 117 348 101 Table A.5 School District Elections, by Type of Measure and Timing Election General Primary Other Tax Bond Total 90 343 433 65 245 310 104 361 465 Even years Odd years 110 464 574 149 485 634 Total 259 949 1,208 102 Appendix B Fiscal Information Fiscal information for local agencies was obtained from the U.S. Bureau of the Census, Census of Governments, Vol. 4, Government Finances, 1972, 1977, 1982, 1987, 1992, and 1997. These include fiscal data for all local governments in the United States including counties, municipalities and townships, school districts, and special districts surveyed by the Bureau of the Census for the U.S. Department of Commerce. Fiscal data for cities came from U.S. Bureau of the Census, Census of Governments, Vol. 4, Government Finances, data file on municipalities and townships. These include specific data for all municipalities and township governments in the United States. These datasets contain information on revenues, expenditures, population, and area for cities but lack demographic information. Demographic information came from the Decennial Population Census data, STF1a files (1980, 1990, and 2000) and the equivalent First Count STF, File B (1970). These are matched to 1972, 1982, and 1992 fiscal data, whereas for the odd years, information is averaged from the available years to 1975, 1985, and 1995 years (to be consistent with the two-year difference). The variables used are personal income (inflated to 2000 dollars), percentage of the population under age 18, over age 65, nonwhite, a homeowner, and has lived in the same house for five years. We have complete fiscal data for all years for 406 cities. If we add the demographic data, the number goes down to 348 cities with complete information for all years (see Table B.1). Here, we look at how these subsamples of cities differ. We divide our sample into all cities excluded for lack of demographic information and cities excluded because they were incorporated after 1972. We explore differences in fiscal policy and size of the cities, for which we look at the average per capita general revenues and population for the different subsamples. 103 Table B.1 Comparison of Cities in and out of Sample 1972 1977 1982 1987 1992 1997 Per Capita General Revenues $ (2000) All California No. of cities Complete information No. of cities Excluded Missing demographics No. of cities Incorporated after 1972 No. of cities 857 1,013 407 413 856 1,007 348 348 945 1,098 1,151 1,175 428 444 460 471 955 1,110 1,179 1,212 348 348 348 348 1,059 59 0 1,802 58 758 7 1,339 58 451 22 2,003 58 705 38 2,314 2,129 58 58 643 723 54 65 Average Size (Population) All California No. of cities Complete information No. of cities Excluded Missing demographics No. of cities Incorporated after 1972 No. of cities 36,905 38,717 42,066 46,933 51,329 54,368 406 413 428 444 460 471 42,893 45,270 50,048 56,736 62,460 66,442 348 348 348 348 348 348 1,589 1,934 2,303 2,788 3,424 4,039 59 58 58 58 58 58 17,720 20,640 24,544 31,048 33,375 0 7 22 38 54 65 Cities included in our sample have very similar per capita general revenues and are somewhat bigger than the overall average in the state. As we might expect, cities incorporated after 1972 and therefore not included in our sample are substantially smaller in terms of both population and average per capita revenues. Cities excluded for lack of demographic information seem to be relatively small cities with a high average per capita expenditure. However, our sample seems to be quite similar to California cities overall (Figure B.1). 104 Revenue dollars (2000) 1,500 1,400 1,300 1,200 1,100 1,000 900 800 700 600 500 1972 1977 1982 1987 Sample California 1992 1997 Figure B.1—Real Per Capita General Revenue for Cities, 1972–1997 105 Appendix C School District Information This appendix includes information on the number of bond measures (Table C.1) and parcel tax measures (Table C.5) proposed and passed by school districts in different counties. It then presents information on the regression estimates used to examine the effect of area demographics on school district bond elections. Table C.2 presents information on the proposal or passage of at least one bond measure. Table C.3 lists the points in the distribution of key variables used to carry out the simulations in Chapter 3. Finally, regressions of the determinants of capital spending are presented in Table C.4. 107 Table C.1 Number of School Districts and Number of Bond Measures Proposed and Passed, by County, 1986–2002 County Alameda Alpine Amador Butte Calaveras Colusa Contra Costa Del Norte El Dorado Fresno Glenn Humboldt Imperial Inyo Kern Kings Lake Lassen Los Angeles Madera Marin Mariposa Mendocino Merced Modoc Mono Monterey Napa Nevada Orange Placer Plumas Riverside Sacramento San Benito San Bernardino San Diego San Francisco San Joaquin San Luis Obispo No. of Districts 18 1 1 14 4 4 18 1 15 34 9 32 16 7 47 14 7 10 81 11 19 1 12 20 3 2 24 5 10 27 19 1 23 16 11 33 43 1 15 10 1986–2000 No. of Measures Passage Proposed Rate (%) 33 73 0 N/A 10 15 20 11 18 30 25 76 10 9 33 39 49 3 67 11 45 18 61 4 75 42 50 16 56 4 50 8 50 98 66 11 27 13 85 20 8 63 11 36 2 50 2 100 18 67 7 43 10 14 79 23 57 1 100 34 41 25 44 2 50 49 41 52 56 4 100 13 38 11 36 2001–2002 No. of Measures Passage Proposed Rate (%) 2 100 0 N/A 1 100 2 100 0 N/A 0 N/A 8 88 0 N/A 2 100 3 100 0 N/A 3 67 2 50 0 N/A 5 80 10 2 100 0 N/A 18 89 1 100 5 100 0 N/A 20 3 67 0 N/A 0 N/A 6 83 1 100 1 100 8 100 5 80 1 100 8 100 10 100 1 100 7 86 11 45 0 N/A 8 63 3 33 108 County San Mateo Santa Barbara Santa Clara Santa Cruz Shasta Sierra Siskiyou Solano Sonoma Stanislaus Sutter Tehama Trinity Tulare Tuolumne Ventura Yolo Yuba Table C.1 (continued) No. of Districts 23 23 33 11 25 1 29 6 40 27 12 18 11 47 12 20 5 5 1986–2000 No. of Measures Passage Proposed Rate (%) 26 81 24 58 48 75 5 60 17 24 0 N/A 5 20 14 43 27 85 29 48 8 25 4 25 0 N/A 20 40 4 50 33 52 13 46 0 N/A 2001–2002 No. of Measures Passage Proposed Rate (%) 6 100 1 100 10 90 3 100 2 100 0 N/A 10 3 100 7 86 8 100 0 N/A 1 100 0 N/A 6 100 2 50 2 100 10 10 109 Table C.2 Determinants of Bond Measure Proposals and Passage Rates, Regression Results Average daily attendance Proposed Any Passed Any Passed Any If Measures Measures Proposed All All All Districts Unified Districts Unified Districts Unified 0.042 0.017 0.027 0.018 0.000 0.011 (0.010) (0.011) (0.008) (0.009) (0.004) (0.012) % growth in average daily 0.224 0.593 0.225 0.450 0.255 0.473 attendance, 1989–1998 (0.107) (0.406) (0.104) (0.327) (0.231) (0.456) Assessed value per student –0.004 –0.047 –0.009 –0.028 –0.008 0.144 (0.005) (0.025) (0.008) (0.024) (0.014) (0.086) Mean household income 0.002 0.013 0.008 0.025 0.037 0.040 (0.003) (0.008) (0.003) (0.008) (0.011) (0.017) % over age 65 –0.942 –0.313 –0.554 0.010 2.496 –0.692 (0.967) (1.915) (0.982) (1.858) (1.959) (2.908) % nonwhite 0.614 0.114 0.416 –0.126 0.161 –0.130 (0.253) (0.457) (0.246) (0.422) (0.416) (0.587) % homeowner 0.439 0.393 –0.725 –2.079 –3.992 –5.314 (0.461) (1.043) (0.457) (0.999) (0.969) (1.837) Elementary school district –0.645 (0.125) –0.324 (0.120) 0.487 (0.180) High school district –0.054 (0.188) 0.132 (0.183) 0.293 (0.259) Northern –0.069 –0.527 –0.262 –0.334 –0.309 –0.056 (0.193) (0.345) (0.192) (0.337) (0.279) (0.434) Bay Area 0.524 0.303 0.615 0.532 0.703 0.248 (0.167) (0.306) (0.159) (0.281) (0.318) (0.451) Valley –0.108 0.105 –0.233 –0.069 –0.127 –0.272 (0.150) (0.286) (0.142) (0.249) (0.213) (0.306) Coastal 0.028 –0.559 0.058 –0.237 0.017 –0.110 (0.244) (0.390) (0.233) (0.365) (0.371) (0.507) Constant –0.393 –0.676 –0.237 –0.079 1.067 1.521 (0.423) (0.939) (0.415) (0.873) (0.885) (1.451) No. of observations 726 246 726 246 431 192 NOTES: Robust standard errors are in parentheses. 110 Table C.3 Distribution of Key Regression Variables Average daily attendance Average daily attendance growth, 1989–1998 Assessed value per student, $ Mean household income, $ % homeowners Median 2,211 119 397,874 40,754 64.7 25th 75th Percentile Percentile 461 7,039 107 255,077 32,712 56.4 132 669,118 51,232 73.1 111 Table C.4 Determinants of Per Pupil Capital Revenue, 1992–2000 Ln average daily attendance Total Capital Revenue per Student All All Districts Unified Districts Unified 0.312 0.132 0.204 0.084 (0.041) (0.059) (0.043) (0.060) Ln growth in average daily attendance 0.429 1.210 0.393 1.158 (0.113) (0.223) (0.110) (0.219) Ln assessed value per student 0.424 0.319 0.355 0.280 (0.092) (0.146) (0.089) (0.144) Ln mean household income –0.217 0.214 –0.218 0.104 (0.219) (0.305) (0.213) (0.301) % over age 65 –1.331 2.098 –1.081 2.329 (1.019) (1.493) (0.989) (1.465) % nonwhite 0.148 0.388 –0.004 0.359 (0.265) (0.329) (0.258) (0.323) % homeowner 0.842 0.046 0.763 0.140 (0.475) (0.735) (0.465) (0.731) Elementary school district 0.094 (0.128) 0.148 (0.125) High school district –0.345 (0.199) –0.297 (0.194) Northern 0.071 –0.088 0.014 –0.046 (0.204) (0.263) (0.199) (0.258) Bay Area 0.721 0.519 0.557 0.466 (0.158) (0.194) (0.155) (0.191) Valley 0.029 0.273 –0.003 0.259 (0.153) (0.193) (0.149) (0.189) Coastal 0.272 0.385 0.210 0.448 (0.245) (0.290) (0.238) (0.285) Proposed any bond measure 0.432 0.346 (0.171) (0.186) Passed any bond measure 0.412 0.247 (0.179) (0.215) Constant 1.056 –1.609 2.451 0.055 (2.234) (2.847) (2.178) (2.842) No. of observations 726 246 726 246 R-squared 0.2 0.25 0.25 0.28 NOTES: Robust standard errors are in parentheses. 112 Table C.5 Number of Parcel Tax Measures Proposed and Passed by School Districts, by County, 1986–2000 County Alameda Alpine Amador Butte Calaveras Colusa Contra Costa Del Norte El Dorado Fresno Glenn Humboldt Imperial Inyo Kern Kings Lake Lassen Los Angeles Madera Marin Mariposa Mendocino Merced Modoc Mono Monterey Napa Nevada Orange Placer Plumas Riverside Sacramento San Benito San Bernardino San Diego San Francisco San Joaquin San Luis Obispo San Mateo Santa Barbara No. of Measures Passage Rate Proposed (%) 16 81 0 N/A 0 N/A 0 N/A 10 0 N/A 20 50 0 N/A 0 N/A 0 N/A 10 10 0 N/A 0 N/A 3 67 0 N/A 0 N/A 0 N/A 24 29 0 N/A 48 85 10 2 50 0 N/A 0 N/A 0 N/A 50 0 N/A 10 30 4 75 0 N/A 0 N/A 10 0 N/A 1 100 30 0 N/A 10 0 N/A 16 69 0 N/A 113 Table C.5 (continued) County Santa Clara Santa Cruz Shasta Sierra Siskiyou Solano Sonoma Stanislaus Sutter Tehama Trinity Tulare Tuolumne Ventura Yolo Yuba No. of Measures Passage Rate Proposed (%) 24 50 6 17 0 N/A 0 N/A 0 N/A 3 33 24 58 0 N/A 0 N/A 0 N/A 0 N/A 6 17 0 N/A 20 4 100 0 N/A 114 Appendix D Municipal Election Information Table D.1 presents information on the distribution of cities and municipal tax elections across counties. It also contains information on the probability of proposing tax measures as well as city revenue demand regressions. Table D.2 estimates a probit model on the probability of proposing or passing at least one tax measure. The revenue and demographic data came from Census of Governments (per capita general revenues and percentage of general revenues coming from property tax) and the Decennial Census (per capita income, population, density, percentage of registered Democrats, percentage homeowners, and percentage living in the same house for five years). Information on the number of special districts in a county came from the California Controllers’ office. Information on the points in the distribution of variables used in the simulations in Chapter 4 are presented in Table D.3. Table D.4 uses a natural log regression model, correcting for within-county heteroskedasticity. All demographic controls came from the Decennial Census. The 1982 and 1992 regressions use 1980 and 1990 Census data, whereas even years have been averaged from Census ones. 115 Table D.1 Number of Tax Measures Proposed and Passed by Cities, 1986–2000 County Alameda Alpine Amador Butte Calaveras Colusa Contra Costa Del Norte El Dorado Fresno Glenn Humboldt Imperial Inyo Kern Kings Lake Lassen Los Angeles Madera Marin Mariposa Mendocino Merced Modoc Mono Monterey Napa Nevada Orange Placer Plumas Riverside Sacramento San Benito San Bernardino San Diego San Francisco San Joaquin San Luis Obispo San Mateo No. of Cities 14 0 5 5 1 2 19 1 2 15 2 7 7 1 11 4 2 1 88 2 11 0 4 6 1 1 12 5 3 33 6 1 24 5 2 24 18 1 7 7 20 No. of Measures Proposed 52 0 1 7 2 1 22 0 3 22 4 7 6 0 13 1 3 0 77 3 39 0 4 2 0 1 21 2 5 19 15 0 36 14 5 26 17 11 1 13 23 Passage Rate (%) 75.0 N/A 100.0 28.6 0.0 100.0 40.9 N/A 66.7 45.5 25.0 14.3 33.3 N/A 15.4 0.0 33.3 N/A 36.4 0.0 69.2 200.0 50.0 100.0 N/A 100.0 52.4 50.0 60.0 31.6 26.7 N/A 30.6 78.6 20.0 23.1 64.7 90.9 0.0 30.8 73.9 116 County Santa Barbara Santa Clara Santa Cruz Shasta Sierra Siskiyou Solano Sonoma Stanislaus Sutter Tehama Trinity Tulare Tuolumne Ventura Yolo Yuba Table D.1 (continued) No. of Cities 7 15 4 3 1 9 7 9 9 2 3 0 8 1 10 4 2 No. of Measures Proposed 7 20 4 2 3 4 9 14 15 3 1 0 0 3 12 8 3 Passage Rate (%) 28.6 50.0 25.0 50.0 0.0 75.0 44.4 50.0 60.0 33.3 0.0 N/A N/A 0.0 33.3 87.5 33.3 117 Table D.2 Determinants of Tax Measure Proposals and Passage Rates, Regression Results 118 City per capita general expenditures, 1977, $1000s (2000) % of city revenues from property tax, 1977 Real per capita income,1990, $1000s (2000) City population, 1990 (millions) Density, 1990 (population per sq. mi.) % registered as Democrat, 1999 % homeowners, 1990 % in same house for 5 years Charter city No. of special districts, 1997 Proposed Any Tax Measures –0.374 (0.179) 1.285 (0.802) 0.330 (0.218) 0.784 (0.705) –0.068 (0.029) 0.018 (0.007) –0.001 (0.009) –0.025 (0.011) –0.159 (0.180) –0.007 (0.003) Proposed Any Tax Measures –0.359 (0.185) 1.528 (0.828) 0.133 (0.280) 1.060 (0.790) –0.053 (0.032) 0.009 (0.009) 0.000 (0.009) –0.026 (0.011) –0.176 (0.185) –0.001 (0.003) Passed Any Tax Measures –0.216 (0.186) 2.882 (0.846) 0.427 (0.227) 1.207 (0.783) –0.087 (0.034) 0.017 (0.007) –0.010 (0.009) –0.006 (0.011) –0.267 (0.194) –0.007 (0.003) Passed Any Tax Measures –0.185 (0.192) 3.199 (0.871) 0.232 (0.285) 1.291 (0.814) –0.063 (0.036) 0.007 (0.009) –0.012 (0.010) –0.006 (0.011) –0.285 (0.196) –0.003 (0.004) Passed Tax If Proposed 0.158 (0.338) 3.304 (1.169) 0.445 (0.317) 1.435 (1.376) –0.067 (0.045) 0.011 (0.010) –0.015 (0.012) 0.013 (0.014) –0.346 (0.262) –0.004 (0.004) Passed Tax If Proposed 0.120 (0.336) 3.437 (1.188) 0.378 (0.398) 1.328 (1.458) –0.047 (0.047) 0.005 (0.013) –0.019 (0.013) 0.014 (0.014) –0.376 (0.271) –0.005 (0.005) Table D.2 (continued) 119 Northern Proposed Any Tax Measures Bay Area Valley Coastal Constant No. of observations NOTES: Robust standard errors are in parentheses. 0.158 (0.880) 348 Proposed Any Tax Measures 0.595 (0.307) 0.654 (0.287) –0.062 (0.236) 0.741 (0.295) 0.416 (1.177) 348 Passed Any Tax Measures –1.540 (0.908) 348 Passed Any Tax Measures 0.477 (0.312) 0.671 (0.294) 0.314 (0.254) 0.157 (0.302) –0.971 (1.219) 348 Passed Tax If Proposed –1.883 (1.283) 203 Passed Tax If Proposed 0.214 (0.380) 0.336 (0.412) 0.516 (0.332) –0.355 (0.375) –1.300 (1.760) 203 Table D.3 Distribution of Key Regression Variables Per capita general revenue, $ % of revenues from property tax Density (population per sq. mi.) % Democrat % in the same house for 5 years No. of special districts Median 698 19.6 3,514 57.1 45.0 48 25th Percentile 535 14.5 2,343 47.3 40.0 29 75th Percentile 899 26.2 5,704 67.4 51.1 93 Table D.4 Demand for City Revenues, Controlling for Which Cities Proposed and Passed Tax Measures Ln population Per Capita General Revenues 1977 1982 1987 1992 1997 0.032 0.053 0.070 0.056 0.022 (0.023) (0.019) (0.018) (0.023) (0.023) Ln real per capita income –0.162 –0.161 0.053 0.112 0.140 (0.145) (0.126) (0.123) (0.134) (0.109) Ln density –0.179 –0.186 –0.189 –0.189 –0.157 (0.066) (0.050) (0.059) (0.078) (0.075) % under age 18 –0.034 –0.044 –0.035 –0.029 –0.035 (0.007) (0.006) (0.006) (0.009) (0.008) % over age 65 –0.005 0.000 0.003 0.003 0.000 (0.007) (0.007) (0.006) (0.005) (0.007) % nonwhite 0.011 0.010 0.007 0.005 0.006 (0.003) (0.002) (0.003) (0.003) (0.003) % in same house for 5 years –0.003 –0.001 –0.008 –0.009 –0.011 (0.003) (0.002) (0.003) (0.003) (0.004) Proposed a tax measure, 1986–2000 –0.116 –0.152 –0.156 –0.165 –0.145 (0.044) (0.033) (0.040) (0.048) (0.047) Passed a tax measure, 1986–2000 0.113 0.095 0.103 0.100 0.126 (0.049) (0.046) (0.054) (0.052) (0.056) Constant 10.416 10.116 8.132 7.689 7.679 (1.552) (1.266) (1.352) (1.530) (1.231) No. of observations 348 348 348 348 348 R-squared 0.21 0.27 0.27 0.24 0.24 NOTE: Robust standard errors are in parentheses. 120 Appendix E County and Special District Election Information This appendix contains information on county and special district elections. Tables E.1 and E.2 present information underlying the maps in Chapter 5. Table E.3 estimates a linear model, at the county level, of the number of ballot measures proposed and passed. Demographic controls came from the Decennial Census. Table E.4 estimates a probit regression on the probability of an election measure passing once proposed using election characteristics as independent variables. 121 Table E.1 Percentage of Direct Expenditures Controlled by Counties, Number of Special Districts, and Number of Tax Measures Proposed and Passed by Special Districts, 1986–2000 County Alameda Alpine Amador Butte Calaveras Colusa Contra Costa Del Norte El Dorado Fresno Glenn Humboldt Imperial Inyo Kern Kings Lake Lassen Los Angeles Madera Marin Mariposa Mendocino Merced Modoc Mono Monterey Napa Nevada Orange Placer Plumas Riverside Sacramento San Benito San Bernardino San Diego San Francisco San Joaquin % of Direct Expenditures Controlled by Counties 42.1 84.7 69.8 60.7 88.3 64.0 51.4 68.6 56.9 54.8 65.8 64.6 46.8 56.9 66.0 57.8 66.2 84.6 53.5 64.3 51.2 77.3 59.0 68.2 83.0 55.0 50.6 63.8 52.0 46.7 52.8 53.8 55.8 70.8 23.7 57.2 42.8 N/A 59.8 Special Districts No. of No. of Measures Passage Districts Proposed Rate (%) 14 9 56 3 10 17 1 0 40 5 0 40 4 50 40 1 0 45 23 39 20 2 100 49 24 42 100 5 40 37 0 N/A 48 5 40 21 2 50 23 7 29 100 15 20 35 1 0 37 5 40 25 12 33 93 9 56 9 20 28 51 57 4 1 100 41 10 50 63 0 N/A 29 9 67 21 3 100 48 12 58 5 3 33 25 15 60 29 7 43 51 19 37 36 10 50 66 8 38 66 8 75 9 2 50 56 22 45 65 38 39 0 00 102 8 13 122 County San Luis Obispo San Mateo Santa Barbara Santa Clara Santa Cruz Shasta Sierra Siskiyou Solano Sonoma Stanislaus Sutter Tehama Trinity Tulare Tuolumne Ventura Yolo Yuba Table E.1 (continued) % of Direct Expenditures Controlled by Counties 62.1 45.0 60.2 52.5 56.0 55.2 60.2 74.1 42.4 53.0 61.1 56.8 81.6 92.7 47.0 90.3 57.5 49.4 75.8 Special Districts No. of No. of Measures Passage Districts Proposed Rate (%) 32 2 0 28 8 88 36 9 22 21 9 89 26 6 67 35 1 100 14 0 N/A 43 11 45 43 1 100 44 14 64 56 2 0 27 13 15 33 1 0 16 5 60 111 5 40 13 10 60 29 3 0 29 0 N/A 41 2 0 123 Table E.2 Number of Tax Measures Proposed and Passed by Non–School District Local Governments, by County, 1986–2000 County Alameda Alpine Amador Butte Calaveras Colusa Contra Costa Del Norte El Dorado Fresno Glenn Humboldt Imperial Inyo Kern Kings Lake Lassen Los Angeles Madera Marin Mariposa Mendocino Merced Modoc Mono Monterey Napa Nevada Orange Placer Plumas Riverside Sacramento San Benito San Bernardino San Diego San Francisco San Joaquin San Luis Obispo San Mateo Santa Barbara No. of Measures Passage Proposed Rate (%) 71 72 10 3 33 17 24 11 18 4 25 54 37 9 33 29 41 30 47 8 13 14 21 11 45 8 38 33 18 20 8 38 13 38 88 40 7 14 94 61 3 67 18 39 4 75 9 67 4 100 37 49 8 63 24 50 30 33 36 31 15 40 45 31 30 57 14 29 52 33 60 47 11 91 11 18 17 24 33 79 17 29 124 Table E.2 (continued) County Santa Clara Santa Cruz Shasta Sierra Siskiyou Solano Sonoma Stanislaus Sutter Tehama Trinity Tulare Tuolumne Ventura Yolo Yuba No. of Measures Passage Proposed Rate (%) 35 66 14 50 5 40 5 40 16 56 14 57 33 48 18 50 19 21 5 40 8 38 5 40 20 45 18 28 9 78 11 9 125 Table E.3 Determinants of Number of Measures Proposed and Passed by Counties, 1986–2000 No. of governments Median Value 40 No. of Measures Proposed 0.178 (0.074) No. of No. of Measures Measures Passed Passed 0.056 –0.042 (0.046) (0.021) Per capita general expenditures, 1997, $1000s (2000) 2 –3.828 –2.464 –0.341 (5.172) (3.178) (1.389) County per capita property tax, 1997, $1000s (2000) 0.417 4.766 2.863 0.219 (15.755) (9.680) (4.212) Real per capita income, 1990, $1000s (2000) 23 1.732 0.972 0.012 (0.343) (0.210) (0.114) County population, 1990 (thousands) 134 0.005 0.002 –0.001 (0.002) (0.001) (0.001) Change in population, 1980 to 1990 27 –0.068 –0.122 –0.085 (0.203) (0.125) (0.054) % homeowners, 1990 62 0.672 0.477 0.104 (0.505) (0.310) (0.137) % living in same house for 5 years, 1990 41 –0.734 –0.427 –0.020 (0.624) (0.383) (0.169) % registered as Democrat, 1990 44 0.239 0.340 0.207 (0.259) (0.159) (0.070) % of population nonwhite 80 –0.166 –0.214 –0.122 (0.268) (0.165) (0.072) Proposed a tax measure in period, 1986–2000 0.555 (0.039) Constant –34.525 –21.391 –2.241 (33.547) (20.611) (9.061) No. of observations 58 58 58 R-squared 0.71 0.66 0.93 NOTE: Robust standard errors are in parentheses. 126 Table E.4 Determinants of the Probability of a Tax Measure Passing Year 1996–1997 Probability of Passing 0.111 (0.112) After 1997 –0.005 (0.095) Primary election 0.073 (0.092) Off-cycle election 0.268 (0.165) Proposed by county –0.227 (0.133) Proposed by special district 0.178 (0.111) Fire protection measure 0.092 (0.176) Emergency services measure –0.169 (0.134) Hospital measure 0.101 (0.246) Parks and recreation measure –0.381 (0.169) Transportation measure 0.339 (0.184) Other function measure (non–general government) 0.005 (0.147) Business tax 0.418 (0.139) Consumer tax –0.083 (0.161) Sales tax –0.162 (0.163) Northern –0.100 (0.119) Bay Area 0.578 (0.109) Valley 0.010 (0.129) 127 Table E.4 (continued) Coastal Probability of Passing 0.105 (0.147) Constant –0.483 (0.150) No. of observations 1,141 NOTE: Robust standard errors are in parentheses. 128 Bibliography Balsdon, Ed, Eric Brunner, and Kim Rueben, “Private Demands for Public Capital: Evidence from California School Bond Measures,” San Diego State University Working Paper, San Diego State University, San Diego, California, 2002. Bergstrom, Theodore C., Daniel L. Rubinfeld, and Perry Shapiro, “Micro-Based Estimates of Demand Functions for Local School Expenditures,” Econometrica, Vol. 50, No. 4, 1982, pp. 1183–1205. Borcherding, Thomas E., and Robert T. Deacon, “The Demand for the Services of Non-Federal Governments,” American Economic Review, Vol. 62, No. 5, 1972, pp. 891–901. Brokaw, Alan J., James R. Gale, and Thomas E. Merz, “The Effect of Tax Price on Voter Choice in Local School Measures: Some New Evidence from Michigan,” National Tax Journal, Vol. 51, No. 1, 2001, pp. 527–540. Brunner, Eric, and Kim S. Rueben, “Financing New School Construction and Modernization: Evidence from California,” National Tax Journal, Vol. 54, No. 3, 2001, pp. 53–60. Cain, Bruce E., Ellyce Cooper, Sara Ferejohn, and Carrie Potter “California Library Measures: The Determinants of Success and Failure,” working paper 96-7, Institute of Government Studies, University of California, Berkeley, California, 1996. California Association of Realtors, California Ballot Monitor: A Guide to Local Land Use and Taxation Measures, Sacramento, California, December 1992. California Debt Advisory Committee, State and Local Tax and Bond Ballot Measures: Summary of Election Results, Sacramento, California, various issues, 1986–2002. 129 California Debt and Investment Advisory Committee, “Local Tax Measures Dominate November Election,” Debt Line, Vol. 16, No. 1, Sacramento, California, 1997. California Senate Committee on Local Governments, An Inventory of Local Tax Powers, Sacramento, California, 1996. Coalition for Adequate School Housing, School District Elections (data file), Sacramento, California, 2002. Dardia, Michael, Subsidizing Redevelopment in California, Public Policy Institute of California, San Francisco, California, 1998. Doerr, David R., California’s Tax Machine: A History of Taxing and Spending in the Golden State, California Taxpayers’ Association, Sacramento, California, 2000. Hajnal, Zoltan L., Paul G. Lewis, and Hugh Louch, Municipal Elections in California: Turnout, Timing, and Competition, Public Policy Institute of California, San Francisco, California, 2002. Legislative Analyst’s Office, A New Blueprint for California School Facility Finance, Sacramento, California, 2001. Lewis, Paul G., Deep Roots: Local Government Structure in California, Public Policy Institute of California, San Francisco, California, 1998. Lewis, Paul G., and Elisa Barbour, California Cities and the Local Sales Tax, Public Policy Institute of California, San Francisco, California, 1999. McGuire, Therese J., and Kim S. Rueben, “Tax and Bond Measures in California and Illinois: Observations on Local Governments Operating under State-Imposed Constraints,” Proceedings of the 89th Annual Conference on Taxation, National Tax Association, Washington, D.C., 1997. O’Sullivan, Arthur, Terri A. Sexton, and Steve Sheffrin, Property Taxes & Tax Revolts: The Legacy of Proposition 13, Cambridge University Press, Cambridge, Massachusetts, 1995. Schrag, Peter, Paradise Lost: California’s Experience, America’s Future, The New Press, New York, 1998. 130 Sears, David O., and Jack Citrin, Tax Revolt: Something for Nothing in California, Harvard University Press, Cambridge, Massachusetts, 1985. Sheffrin, Steven M., and Terri Sexton, Proposition 13 in Recession and Recovery, Public Policy Institute of California, San Francisco, California, 1998. Sonstelie, Jon, Eric Brunner, and Ken Ardon, For Better or For Worse? School Finance Reform in California, Public Policy Institute of California, San Francisco, California, 2000. Sonstelie, Jon, and Peter Richardson (eds.), School Finance and California’s Master Plan for Education, Public Policy Institute of California, San Francisco, California, 2001. U.S. Bureau of the Census, Census of Governments: Volume 4, Government Finances (machine-readable data files), Washington, D.C., 1972, 1977, 1982, 1987, 1992, and 1997. U.S. Department of Education, National Center for Education Statistics, School District Data Book (SDDB) (computer file), Washington, D.C., 1990. 131 About the Authors KIM S. RUEBEN Kim S. Rueben is a research fellow at the Public Policy Institute of California, where she studies public finance, state and local government budget decisions, and school resources. Her co-authored publications include Equal Resources, Equal Outcomes? The Distribution of School Resources and Student Achievement in California (2000) and Fiscal Rules and State Borrowing Costs: Evidence from California and Other States (1999). She is currently investigating facilities financing in California school districts. She holds a B.S. in applied math–economics from Brown University, an M.A. in economics from the London School of Economics, and a Ph.D. in economics from the Massachusetts Institute of Technology. PEDRO CERDÁN Pedro Cerdán is a research associate at the Public Policy Institute of California. His research interests include educational issues, economic development, and poverty and inequality. He holds a B.A. in economics, specializing in quantitative methods, from the Universitat Pompeu Fabra, Barcelona, Spain. 133 Related PPIC Publications A California State of Mind: The Conflicted Voter in a Changing World Mark Baldassare Municipal Elections in California: Turnout, Timing, and Competition Zoltan L. Hajnal, Paul G. Lewis, and Hugh Louch California Cities and the Local Sales Tax Paul G. Lewis and Elisa Barbour Has Proposition 13 Delivered? The Changing Tax Burden in California Michael A. Shires, John Ellwood, and Mary Sprague The State-Local Fiscal Relationship in California: A Changing Balance of Power J. Fred Silva and Elisa Barbour PPIC publications may be ordered by phone or from our website (800) 232-5343 [mainland U.S.] (415) 291-4400 [Canada, Hawaii, overseas] www.ppic.org 135" ["post_date_gmt"]=> string(19) "2017-05-20 09:36:26" ["comment_status"]=> string(4) "open" ["ping_status"]=> string(6) "closed" ["post_password"]=> string(0) "" ["post_name"]=> string(8) "r_103krr" ["to_ping"]=> string(0) "" ["pinged"]=> string(0) "" ["post_modified"]=> string(19) "2017-05-20 02:36:26" ["post_modified_gmt"]=> string(19) "2017-05-20 09:36:26" ["post_content_filtered"]=> string(0) "" ["guid"]=> string(50) "http://148.62.4.17/wp-content/uploads/R_103KRR.pdf" ["menu_order"]=> int(0) ["post_mime_type"]=> string(15) "application/pdf" ["comment_count"]=> string(1) "0" ["filter"]=> string(3) "raw" ["status"]=> string(7) "inherit" ["attachment_authors"]=> bool(false) }